Simultaneous Localization and Surveying with Multiple Agents. - Sam T. Roweis; Ruslan Salakhutdinov (European Summer School on Multi-AgentControl, 2003)

Adaptive Overrelaxed Bound Optimization Methods. - Ruslan Salakhutdinov; Sam T. Roweis (ICML, 2003)

Optimization with EM and Expectation-Conjugate-Gradient. - Ruslan Salakhutdinov; Sam T. Roweis; Zoubin Ghahramani (ICML, 2003)

On the Convergence of Bound Optimization Algorithms. - Ruslan Salakhutdinov; Sam T. Roweis; Zoubin Ghahramani (UAI, 2003)

Semi-Supervised Mixture-of-Experts Classification. - Grigoris I. Karakoulas; Ruslan Salakhutdinov (ICDM, 2004)

Neighbourhood Components Analysis. - Jacob Goldberger; Sam T. Roweis; Geoffrey E. Hinton; Ruslan Salakhutdinov (NIPS, 2004)

Restricted Boltzmann machines for collaborative filtering. - Ruslan Salakhutdinov; Andriy Mnih; Geoffrey E. Hinton (ICML, 2007)

Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes. - Ruslan Salakhutdinov; Geoffrey E. Hinton (NIPS, 2007)

Probabilistic Matrix Factorization. - Ruslan Salakhutdinov; Andriy Mnih (NIPS, 2007)

Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure. - Ruslan Salakhutdinov; Geoffrey E. Hinton (AISTATS, 2007)

On the quantitative analysis of deep belief networks. - Ruslan Salakhutdinov; Iain Murray 001 (ICML, 2008)

Bayesian probabilistic matrix factorization using Markov chain Monte Carlo. - Ruslan Salakhutdinov; Andriy Mnih (ICML, 2008)

Evaluating probabilities under high-dimensional latent variable models. - Iain Murray 001; Ruslan Salakhutdinov (NIPS, 2008)

Learning nonlinear dynamic models. - John Langford 001; Ruslan Salakhutdinov; Tong Zhang 001 (ICML, 2009)

Evaluation methods for topic models. - Hanna M. Wallach; Iain Murray 001; Ruslan Salakhutdinov; David M. Mimno (ICML, 2009)

Workshop summary: Workshop on learning feature hierarchies. - Kai Yu; Ruslan Salakhutdinov; Yann LeCun; Geoffrey E. Hinton; Yoshua Bengio (ICML, 2009)

Learning in Markov Random Fields using Tempered Transitions. - Ruslan Salakhutdinov (NIPS, 2009)

Replicated Softmax: an Undirected Topic Model. - Ruslan Salakhutdinov; Geoffrey E. Hinton (NIPS, 2009)

Modelling Relational Data using Bayesian Clustered Tensor Factorization. - Ilya Sutskever; Ruslan Salakhutdinov; Joshua B. Tenenbaum (NIPS, 2009)

Semantic hashing. - Ruslan Salakhutdinov; Geoffrey E. Hinton (Int. J. Approx. Reason., 2009)

Deep Boltzmann Machines. - Ruslan Salakhutdinov; Geoffrey E. Hinton (AISTATS, 2009)

Learning Deep Boltzmann Machines using Adaptive MCMC. - Ruslan Salakhutdinov (ICML, 2010)

Practical Large-Scale Optimization for Max-norm Regularization. - Jason D. Lee; Ben Recht; Ruslan Salakhutdinov; Nathan Srebro; Joel A. Tropp (NIPS, 2010)

Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm. - Ruslan Salakhutdinov; Nathan Srebro (NIPS, 2010)

Efficient Learning of Deep Boltzmann Machines. - Ruslan Salakhutdinov; Hugo Larochelle (AISTATS, 2010)

Learning Deep Generative Models. - Ruslan Salakhutdinov (2010)

One shot learning of simple visual concepts. - Brenden M. Lake; Ruslan Salakhutdinov; Jason Gross; Joshua B. Tenenbaum (CogSci, 2011)

Learning to share visual appearance for multiclass object detection. - Ruslan Salakhutdinov; Antonio Torralba 001; Joshua B. Tenenbaum (CVPR, 2011)

Learning with the weighted trace-norm under arbitrary sampling distributions. - Rina Foygel; Ruslan Salakhutdinov; Ohad Shamir; Nati Srebro (NIPS, 2011)

Transfer Learning by Borrowing Examples for Multiclass Object Detection. - Joseph J. Lim; Ruslan Salakhutdinov; Antonio Torralba 001 (NIPS, 2011)

Learning to Learn with Compound HD Models. - Ruslan Salakhutdinov; Joshua B. Tenenbaum; Antonio Torralba 001 (NIPS, 2011)

Domain Adaptation: Overfitting and Small Sample Statistics - Dean P. Foster; Sham M. Kakade; Ruslan Salakhutdinov (CoRR, 2011)

Discovering Binary Codes for Documents by Learning Deep Generative Models. - Geoffrey E. Hinton; Ruslan Salakhutdinov (Top. Cogn. Sci., 2011)

Concept learning as motor program induction: A large-scale empirical study. - Brenden M. Lake; Ruslan Salakhutdinov; Joshua B. Tenenbaum (CogSci, 2012)

Robust Boltzmann Machines for recognition and denoising. - Yichuan Tang; Ruslan Salakhutdinov; Geoffrey E. Hinton (CVPR, 2012)

Resource configurable spoken query detection using Deep Boltzmann Machines. - Yaodong Zhang; Ruslan Salakhutdinov; Hung-An Chang; James R. Glass (ICASSP, 2012)

Deep Mixtures of Factor Analysers. - Yichuan Tang; Ruslan Salakhutdinov; Geoffrey E. Hinton (ICML, 2012)

Deep Lambertian Networks. - Yichuan Tang; Ruslan Salakhutdinov; Geoffrey E. Hinton (ICML, 2012)

Hamming Distance Metric Learning. - Mohammad Norouzi 002; David J. Fleet; Ruslan Salakhutdinov (NIPS, 2012)

Matrix reconstruction with the local max norm. - Rina Foygel; Nathan Srebro; Ruslan Salakhutdinov (NIPS, 2012)

A Better Way to Pretrain Deep Boltzmann Machines. - Ruslan Salakhutdinov; Geoffrey E. Hinton (NIPS, 2012)

Cardinality Restricted Boltzmann Machines. - Kevin Swersky; Daniel Tarlow; Ilya Sutskever; Ruslan Salakhutdinov; Richard S. Zemel; Ryan P. Adams (NIPS, 2012)

Exploiting compositionality to explore a large space of model structures. - Roger B. Grosse; Ruslan Salakhutdinov; William T. Freeman; Joshua B. Tenenbaum (UAI, 2012)

Improving neural networks by preventing co-adaptation of feature detectors - Geoffrey E. Hinton; Nitish Srivastava; Alex Krizhevsky; Ilya Sutskever; Ruslan Salakhutdinov (CoRR, 2012)

Domain Adaptation: A Small Sample Statistical Approach. - Ruslan Salakhutdinov; Sham M. Kakade; Dean P. Foster (AISTATS, 2012)

One-Shot Learning with a Hierarchical Nonparametric Bayesian Model. - Ruslan Salakhutdinov; Joshua B. Tenenbaum; Antonio Torralba 001 (ICML Unsupervised and Transfer Learning, 2012)

An Efficient Learning Procedure for Deep Boltzmann Machines. - Ruslan Salakhutdinov; Geoffrey E. Hinton (Neural Comput., 2012)

Tensor Analyzers. - Yichuan Tang; Ruslan Salakhutdinov; Geoffrey E. Hinton (ICML (3), 2013)

Annealing between distributions by averaging moments. - Roger B. Grosse; Chris J. Maddison; Ruslan Salakhutdinov (NIPS, 2013)

One-shot learning by inverting a compositional causal process. - Brenden M. Lake; Ruslan Salakhutdinov; Joshua B. Tenenbaum (NIPS, 2013)

The Power of Asymmetry in Binary Hashing. - Behnam Neyshabur; Nati Srebro; Ruslan Salakhutdinov; Yury Makarychev; Payman Yadollahpour (NIPS, 2013)

Discriminative Transfer Learning with Tree-based Priors. - Nitish Srivastava; Ruslan Salakhutdinov (NIPS, 2013)

Learning Stochastic Feedforward Neural Networks. - Yichuan Tang; Ruslan Salakhutdinov (NIPS, 2013)

Modeling Documents with Deep Boltzmann Machines. - Nitish Srivastava; Ruslan Salakhutdinov; Geoffrey E. Hinton (UAI, 2013)

Guest Editors' Introduction: Special Section on Learning Deep Architectures. - Samy Bengio; Li Deng 001; Hugo Larochelle; Honglak Lee; Ruslan Salakhutdinov (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Learning with Hierarchical-Deep Models. - Ruslan Salakhutdinov; Joshua B. Tenenbaum; Antonio Torralba 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Multimodal Neural Language Models. - Ryan Kiros; Ruslan Salakhutdinov; Richard S. Zemel (ICML, 2014)

Deep learning. - Ruslan Salakhutdinov (KDD, 2014)

A Multiplicative Model for Learning Distributed Text-Based Attribute Representations. - Ryan Kiros; Richard S. Zemel; Ruslan Salakhutdinov (NIPS, 2014)

Learning Generative Models with Visual Attention. - Yichuan Tang; Nitish Srivastava; Ruslan Salakhutdinov (NIPS, 2014)

BBN VISER TRECVID 2014 Multimedia Event Detection and Multimedia Event Recounting Systems. - Florian Luisier; Manasvi Tickoo; Walter Andrews; Guangnan Ye; Dong Liu 001; Shih-Fu Chang; Ruslan Salakhutdinov; Vlad I. Morariu; Larry Davis 001; Abhinav Gupta 001; Ismail Haritaoglu; Sadiye Guler; et al. (TRECVID, 2014)

Multi-task Neural Networks for QSAR Predictions. - George E. Dahl; Navdeep Jaitly; Ruslan Salakhutdinov (CoRR, 2014)

Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models. - Ryan Kiros; Ruslan Salakhutdinov; Richard S. Zemel (CoRR, 2014)

Deep learning for neuroimaging: a validation study. - Sergey M. Plis; R. Devon Hjelm; Ruslan Salakhutdinov; Vince D. Calhoun (ICLR (Workshop Poster), 2014)

Dropout: a simple way to prevent neural networks from overfitting. - Nitish Srivastava; Geoffrey E. Hinton; Alex Krizhevsky; Ilya Sutskever; Ruslan Salakhutdinov (J. Mach. Learn. Res., 2014)

Multimodal learning with deep Boltzmann machines. - Nitish Srivastava; Ruslan Salakhutdinov (J. Mach. Learn. Res., 2014)

Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks. - R. Devon Hjelm; Vince D. Calhoun; Ruslan Salakhutdinov; Elena A. Allen; Tülay Adali; Sergey M. Plis (NeuroImage, 2014)

Accurate and conservative estimates of MRF log-likelihood using reverse annealing. - Yuri Burda; Roger B. Grosse; Ruslan Salakhutdinov (AISTATS, 2015)

Exploiting Image-trained CNN Architectures for Unconstrained Video Classification. - Shengxin Zha; Florian Luisier; Walter Andrews; Nitish Srivastava; Ruslan Salakhutdinov (BMVC, 2015)

segDeepM: Exploiting segmentation and context in deep neural networks for object detection. - Yukun Zhu; Raquel Urtasun; Ruslan Salakhutdinov; Sanja Fidler (CVPR, 2015)

Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions. - Lei Jimmy Ba; Kevin Swersky; Sanja Fidler; Ruslan Salakhutdinov (ICCV, 2015)

Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books. - Yukun Zhu; Ryan Kiros; Richard S. Zemel; Ruslan Salakhutdinov; Raquel Urtasun; Antonio Torralba 001; Sanja Fidler (ICCV, 2015)

Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix. - Roger B. Grosse; Ruslan Salakhutdinov (ICML, 2015)

Unsupervised Learning of Video Representations using LSTMs. - Nitish Srivastava; Elman Mansimov; Ruslan Salakhutdinov (ICML, 2015)

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. - Kelvin Xu; Jimmy Ba; Ryan Kiros; Kyunghyun Cho; Aaron C. Courville; Ruslan Salakhutdinov; Richard S. Zemel; Yoshua Bengio (ICML, 2015)

Learning Wake-Sleep Recurrent Attention Models. - Jimmy Ba; Ruslan Salakhutdinov; Roger B. Grosse; Brendan J. Frey (NIPS, 2015)

Skip-Thought Vectors. - Ryan Kiros; Yukun Zhu; Ruslan Salakhutdinov; Richard S. Zemel; Raquel Urtasun; Antonio Torralba 001; Sanja Fidler (NIPS, 2015)

Path-SGD: Path-Normalized Optimization in Deep Neural Networks. - Behnam Neyshabur; Ruslan Salakhutdinov; Nathan Srebro (NIPS, 2015)

Iterative Refinement of Approximate Posterior for Training Directed Belief Networks. - R. Devon Hjelm; Kyunghyun Cho; Junyoung Chung; Ruslan Salakhutdinov; Vince D. Calhoun; Nebojsa Jojic (CoRR, 2015)

Initialization Strategies of Spatio-Temporal Convolutional Neural Networks. - Elman Mansimov; Nitish Srivastava; Ruslan Salakhutdinov (CoRR, 2015)

Action Recognition using Visual Attention. - Shikhar Sharma 001; Ryan Kiros; Ruslan Salakhutdinov (CoRR, 2015)

Deep Kernel Learning. - Andrew Gordon Wilson; Zhiting Hu; Ruslan Salakhutdinov; Eric P. Xing (AISTATS, 2016)

Deep Neural Networks with Massive Learned Knowledge. - Zhiting Hu; Zichao Yang; Ruslan Salakhutdinov; Eric P. Xing (EMNLP, 2016)

Revisiting Semi-Supervised Learning with Graph Embeddings. - Zhilin Yang; William W. Cohen; Ruslan Salakhutdinov (ICML, 2016)

Iterative Refinement of the Approximate Posterior for Directed Belief Networks. - R. Devon Hjelm; Russ Salakhutdinov; Kyunghyun Cho; Nebojsa Jojic; Vince D. Calhoun; Junyoung Chung (NIPS, 2016)

Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations. - Behnam Neyshabur; Yuhuai Wu; Ruslan Salakhutdinov; Nati Srebro (NIPS, 2016)

Stochastic Variational Deep Kernel Learning. - Andrew Gordon Wilson; Zhiting Hu; Ruslan Salakhutdinov; Eric P. Xing (NIPS, 2016)

On Multiplicative Integration with Recurrent Neural Networks. - Yuhuai Wu; Saizheng Zhang; Ying Zhang 033; Yoshua Bengio; Ruslan Salakhutdinov (NIPS, 2016)

Review Networks for Caption Generation. - Zhilin Yang; Ye Yuan; Yuexin Wu; William W. Cohen; Ruslan Salakhutdinov (NIPS, 2016)

Architectural Complexity Measures of Recurrent Neural Networks. - Saizheng Zhang; Yuhuai Wu; Tong Che; Zhouhan Lin; Roland Memisevic; Ruslan Salakhutdinov; Yoshua Bengio (NIPS, 2016)

Importance Weighted Autoencoders. - Yuri Burda; Roger B. Grosse; Ruslan Salakhutdinov (ICLR (Poster), 2016)

Gated-Attention Readers for Text Comprehension. - Bhuwan Dhingra; Hanxiao Liu; William W. Cohen; Ruslan Salakhutdinov (CoRR, 2016)

Generating Images from Captions with Attention. - Elman Mansimov; Emilio Parisotto; Lei Jimmy Ba; Ruslan Salakhutdinov (ICLR, 2016)

Data-Dependent Path Normalization in Neural Networks. - Behnam Neyshabur; Ryota Tomioka; Ruslan Salakhutdinov; Nathan Srebro (ICLR (Poster), 2016)

Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning. - Emilio Parisotto; Lei Jimmy Ba; Ruslan Salakhutdinov (ICLR (Poster), 2016)

Multi-Task Cross-Lingual Sequence Tagging from Scratch. - Zhilin Yang; Ruslan Salakhutdinov; William W. Cohen (CoRR, 2016)

Encode, Review, and Decode: Reviewer Module for Caption Generation. - Zhilin Yang; Ye Yuan; Yuexin Wu; Ruslan Salakhutdinov; William W. Cohen (CoRR, 2016)

Gated-Attention Readers for Text Comprehension. - Bhuwan Dhingra; Hanxiao Liu; Zhilin Yang; William W. Cohen; Ruslan Salakhutdinov (ACL (1), 2017)

Semi-Supervised QA with Generative Domain-Adaptive Nets. - Zhilin Yang; Junjie Hu 001; Ruslan Salakhutdinov; William W. Cohen (ACL (1), 2017)

Spatially Adaptive Computation Time for Residual Networks. - Michael Figurnov; Maxwell D. Collins; Yukun Zhu; Li Zhang 003; Jonathan Huang; Dmitry P. Vetrov; Ruslan Salakhutdinov (CVPR, 2017)

The More You Know: Using Knowledge Graphs for Image Classification. - Kenneth Marino; Ruslan Salakhutdinov; Abhinav Gupta 001 (CVPR, 2017)

Learning Robust Visual-Semantic Embeddings. - Yao-Hung Hubert Tsai; Liang-Kang Huang; Ruslan Salakhutdinov (ICCV, 2017)

Deep Determinantal Point Process for Large-Scale Multi-label Classification. - Pengtao Xie; Ruslan Salakhutdinov; Luntian Mou; Eric P. Xing (ICCV, 2017)

On the Quantitative Analysis of Decoder-Based Generative Models. - Yuhuai Wu; Yuri Burda; Ruslan Salakhutdinov; Roger B. Grosse (ICLR (Poster), 2017)

Words or Characters? Fine-grained Gating for Reading Comprehension. - Zhilin Yang; Bhuwan Dhingra; Ye Yuan; Junjie Hu 001; William W. Cohen; Ruslan Salakhutdinov (ICLR (Poster), 2017)

Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks. - Zhilin Yang; Ruslan Salakhutdinov; William W. Cohen (ICLR (Poster), 2017)

Toward Controlled Generation of Text. - Zhiting Hu; Zichao Yang; Xiaodan Liang; Ruslan Salakhutdinov; Eric P. Xing (ICML, 2017)

Improved Variational Autoencoders for Text Modeling using Dilated Convolutions. - Zichao Yang; Zhiting Hu; Ruslan Salakhutdinov; Taylor Berg-Kirkpatrick (ICML, 2017)

Good Semi-supervised Learning That Requires a Bad GAN. - Zihang Dai; Zhilin Yang; Fan Yang 058; William W. Cohen; Ruslan Salakhutdinov (NIPS, 2017)

Deep Sets. - Manzil Zaheer; Satwik Kottur; Siamak Ravanbakhsh; Barnabás Póczos; Ruslan Salakhutdinov; Alexander J. Smola (NIPS, 2017)

A Comparative Study of Word Embeddings for Reading Comprehension. - Bhuwan Dhingra; Hanxiao Liu; Ruslan Salakhutdinov; William W. Cohen (CoRR, 2017)

Linguistic Knowledge as Memory for Recurrent Neural Networks. - Bhuwan Dhingra; Zhilin Yang; William W. Cohen; Ruslan Salakhutdinov (CoRR, 2017)

Controllable Text Generation. - Zhiting Hu; Zichao Yang; Xiaodan Liang; Ruslan Salakhutdinov; Eric P. Xing (CoRR, 2017)

Geometry of Optimization and Implicit Regularization in Deep Learning. - Behnam Neyshabur; Ryota Tomioka; Ruslan Salakhutdinov; Nathan Srebro (CoRR, 2017)

Question Answering from Unstructured Text by Retrieval and Comprehension. - Yusuke Watanabe; Bhuwan Dhingra; Ruslan Salakhutdinov (CoRR, 2017)

Normalized Gradient with Adaptive Stepsize Method for Deep Neural Network Training. - Adams Wei Yu; Qihang Lin; Ruslan Salakhutdinov; Jaime G. Carbonell (CoRR, 2017)

Improving One-Shot Learning through Fusing Side Information. - Yao-Hung Hubert Tsai; Ruslan Salakhutdinov (CoRR, 2017)

Discovering Order in Unordered Datasets: Generative Markov Networks. - Yao-Hung Hubert Tsai; Han Zhao 002; Ruslan Salakhutdinov; Nebojsa Jojic (CoRR, 2017)

Knowledge-based Word Sense Disambiguation using Topic Models. - Devendra Singh Chaplot; Ruslan Salakhutdinov (AAAI, 2018)

Gated-Attention Architectures for Task-Oriented Language Grounding. - Devendra Singh Chaplot; Kanthashree Mysore Sathyendra; Rama Kumar Pasumarthi; Dheeraj Rajagopal; Ruslan Salakhutdinov (AAAI, 2018)

Style Transfer Through Back-Translation. - Shrimai Prabhumoye; Yulia Tsvetkov; Ruslan Salakhutdinov; Alan W. Black (ACL (1), 2018)

Learning Cognitive Models Using Neural Networks. - Devendra Singh Chaplot; Christopher MacLellan; Ruslan Salakhutdinov; Kenneth R. Koedinger (AIED (1), 2018)

A Generic Approach for Escaping Saddle points. - Sashank J. Reddi; Manzil Zaheer; Suvrit Sra; Barnabás Póczos; Francis R. Bach; Ruslan Salakhutdinov; Alexander J. Smola (AISTATS, 2018)

Investigating the Working of Text Classifiers. - Devendra Singh Sachan; Manzil Zaheer; Ruslan Salakhutdinov (COLING, 2018)

Global Pose Estimation With an Attention-Based Recurrent Network. - Emilio Parisotto; Devendra Singh Chaplot; Jian Zhang 050; Ruslan Salakhutdinov (CVPR Workshops, 2018)

Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text. - Haitian Sun; Bhuwan Dhingra; Manzil Zaheer; Kathryn Mazaitis; Ruslan Salakhutdinov; William W. Cohen (EMNLP, 2018)

HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. - Zhilin Yang; Peng Qi 003; Saizheng Zhang; Yoshua Bengio; William W. Cohen; Ruslan Salakhutdinov; Christopher D. Manning (EMNLP, 2018)

Active Neural Localization. - Devendra Singh Chaplot; Emilio Parisotto; Ruslan Salakhutdinov (ICLR (Poster), 2018)

On Unifying Deep Generative Models. - Zhiting Hu; Zichao Yang; Ruslan Salakhutdinov; Eric P. Xing (ICLR (Poster), 2018)

LSTM Iteration Networks: An Exploration of Differentiable Path Finding. - Lisa Lee; Emilio Parisotto; Devendra Singh Chaplot; Ruslan Salakhutdinov (ICLR (Workshop), 2018)

Neural Map: Structured Memory for Deep Reinforcement Learning. - Emilio Parisotto; Ruslan Salakhutdinov (ICLR (Poster), 2018)

Selecting the Best in GANs Family: a Post Selection Inference Framework. - Yao-Hung Hubert Tsai; Denny Wu; Makoto Yamada; Ruslan Salakhutdinov; Ichiro Takeuchi; Kenji Fukumizu (ICLR (Workshop), 2018)

Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. - Zhilin Yang; Zihang Dai; Ruslan Salakhutdinov; William W. Cohen (ICLR, 2018)

Gated Path Planning Networks. - Lisa Lee; Emilio Parisotto; Devendra Singh Chaplot; Eric P. Xing; Ruslan Salakhutdinov (ICML, 2018)

Transformation Autoregressive Networks. - Junier B. Oliva; Avinava Dubey; Manzil Zaheer; Barnabás Póczos; Ruslan Salakhutdinov; Eric P. Xing; Jeff Schneider 001 (ICML, 2018)

Structured Control Nets for Deep Reinforcement Learning. - Mario Srouji; Jian Zhang 050; Ruslan Salakhutdinov (ICML, 2018)

Neural Models for Reasoning over Multiple Mentions Using Coreference. - Bhuwan Dhingra; Qiao Jin 001; Zhilin Yang; William W. Cohen; Ruslan Salakhutdinov (NAACL-HLT (2), 2018)

How Many Samples are Needed to Estimate a Convolutional Neural Network? - Simon S. Du; Yining Wang 001; Xiyu Zhai; Sivaraman Balakrishnan; Ruslan Salakhutdinov; Aarti Singh (NeurIPS, 2018)

Deep Generative Models with Learnable Knowledge Constraints. - Zhiting Hu; Zichao Yang; Ruslan Salakhutdinov; Lianhui Qin; Xiaodan Liang; Haoye Dong; Eric P. Xing (NeurIPS, 2018)

GLoMo: Unsupervised Learning of Transferable Relational Graphs. - Zhilin Yang; Junbo Jake Zhao; Bhuwan Dhingra; Kaiming He; William W. Cohen; Ruslan Salakhutdinov; Yann LeCun (NeurIPS, 2018)

Informedia @ TRECVID 2018: Ad-hoc Video Search, Video to Text Description, Activities in Extended video. - Jia Chen 001; Shizhe Chen; Qin Jin; Alexander G. Hauptmann; Po-Yao Huang 001; Junwei Liang 001; Vaibhav; Xiaojun Chang; Jiang Liu 011; Ting-Yao Hu; Wenhe Liu; Wei Ke; et al. (TRECVID, 2018)

On Characterizing the Capacity of Neural Networks using Algebraic Topology. - William H. Guss; Ruslan Salakhutdinov (CoRR, 2018)

"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study. - Denny Wu; Yixiu Zhao; Yao-Hung Hubert Tsai; Makoto Yamada; Ruslan Salakhutdinov (CoRR, 2018)

How Many Samples are Needed to Learn a Convolutional Neural Network? - Simon S. Du; Yining Wang 001; Xiyu Zhai; Sivaraman Balakrishnan; Ruslan Salakhutdinov; Aarti Singh (CoRR, 2018)

Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex. - Hongyang Zhang 001; Junru Shao; Ruslan Salakhutdinov (CoRR, 2018)

GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations. - Zhilin Yang; Junbo Jake Zhao; Bhuwan Dhingra; Kaiming He; William W. Cohen; Ruslan Salakhutdinov; Yann LeCun (CoRR, 2018)

Style Transfer Through Multilingual and Feedback-Based Back-Translation. - Shrimai Prabhumoye; Yulia Tsvetkov; Alan W. Black; Ruslan Salakhutdinov (CoRR, 2018)

AutoLoss: Learning Discrete Schedules for Alternate Optimization. - Haowen Xu; Hao Zhang 025; Zhiting Hu; Xiaodan Liang; Ruslan Salakhutdinov; Eric P. Xing (CoRR, 2018)

On the Complexity of Exploration in Goal-Driven Navigation. - Maruan Al-Shedivat; Lisa Lee; Ruslan Salakhutdinov; Eric P. Xing (CoRR, 2018)

Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures. - Hongyang Zhang 001; Susu Xu; Jiantao Jiao; Pengtao Xie; Ruslan Salakhutdinov; Eric P. Xing (CoRR, 2018)

Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function. - Devendra Singh Sachan; Manzil Zaheer; Ruslan Salakhutdinov (AAAI, 2019)

Transformer-XL: Attentive Language Models beyond a Fixed-Length Context. - Zihang Dai; Zhilin Yang; Yiming Yang; Jaime G. Carbonell; Quoc Viet Le; Ruslan Salakhutdinov (ACL (1), 2019)

Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization. - Paul Pu Liang; Zhun Liu; Yao-Hung Hubert Tsai; Qibin Zhao; Ruslan Salakhutdinov; Louis-Philippe Morency (ACL (1), 2019)

Multimodal Transformer for Unaligned Multimodal Language Sequences. - Yao-Hung Hubert Tsai; Shaojie Bai; Paul Pu Liang; J. Zico Kolter; Louis-Philippe Morency; Ruslan Salakhutdinov (ACL (1), 2019)

Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex. - Hongyang Zhang 001; Junru Shao; Ruslan Salakhutdinov (AISTATS, 2019)

Worst Cases Policy Gradients. - Yichuan Charlie Tang; Jian Zhang 050; Ruslan Salakhutdinov (CoRL, 2019)

Video Relationship Reasoning Using Gated Spatio-Temporal Energy Graph. - Yao-Hung Hubert Tsai; Santosh Kumar Divvala; Louis-Philippe Morency; Ruslan Salakhutdinov; Ali Farhadi (CVPR, 2019)

Transformer Dissection: An Unified Understanding for Transformer's Attention via the Lens of Kernel. - Yao-Hung Hubert Tsai; Shaojie Bai; Makoto Yamada; Louis-Philippe Morency; Ruslan Salakhutdinov (EMNLP/IJCNLP (1), 2019)

Point Cloud GAN. - Chun-Liang Li; Manzil Zaheer; Yang Zhang; Barnabás Póczos; Ruslan Salakhutdinov (DGS@ICLR, 2019)

Connecting the Dots Between MLE and RL for Sequence Generation. - Bowen Tan; Zhiting Hu; Zichao Yang; Ruslan Salakhutdinov; Eric P. Xing (DeepRLStructPred@ICLR, 2019)

Learning Factorized Multimodal Representations. - Yao-Hung Hubert Tsai; Paul Pu Liang; Amir Zadeh 001; Louis-Philippe Morency; Ruslan Salakhutdinov (ICLR (Poster), 2019)

AutoLoss: Learning Discrete Schedule for Alternate Optimization. - Haowen Xu; Hao Zhang 025; Zhiting Hu; Xiaodan Liang; Ruslan Salakhutdinov; Eric P. Xing (ICLR (Poster), 2019)

Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator. - Makoto Yamada; Denny Wu; Yao-Hung Hubert Tsai; Hirofumi Ohta; Ruslan Salakhutdinov; Ichiro Takeuchi; Kenji Fukumizu (ICLR (Poster), 2019)

MineRL: A Large-Scale Dataset of Minecraft Demonstrations. - William H. Guss; Brandon Houghton; Nicholay Topin; Phillip Wang; Cayden Codel; Manuela Veloso; Ruslan Salakhutdinov (IJCAI, 2019)

Integrating Domain-Knowledge into Deep Learning. - Ruslan Salakhutdinov (KDD, 2019)

Strong and Simple Baselines for Multimodal Utterance Embeddings. - Paul Pu Liang; Yao Chong Lim; Yao-Hung Hubert Tsai; Ruslan Salakhutdinov; Louis-Philippe Morency (NAACL-HLT (1), 2019)

Learning Neural Networks with Adaptive Regularization. - Han Zhao 002; Yao-Hung Hubert Tsai; Ruslan Salakhutdinov; Geoffrey J. Gordon (NeurIPS, 2019)

On Exact Computation with an Infinitely Wide Neural Net. - Sanjeev Arora; Simon S. Du; Wei Hu 014; Zhiyuan Li 005; Ruslan Salakhutdinov; Ruosong Wang (NeurIPS, 2019)

Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels. - Simon S. Du; Kangcheng Hou; Ruslan Salakhutdinov; Barnabás Póczos; Ruosong Wang; Keyulu Xu (NeurIPS, 2019)

Search on the Replay Buffer: Bridging Planning and Reinforcement Learning. - Ben Eysenbach; Ruslan Salakhutdinov; Sergey Levine (NeurIPS, 2019)

Learning Data Manipulation for Augmentation and Weighting. - Zhiting Hu; Bowen Tan; Ruslan Salakhutdinov; Tom M. Mitchell; Eric P. Xing (NeurIPS, 2019)

Deep Gamblers: Learning to Abstain with Portfolio Theory. - Ziyin Liu; Zhikang Wang; Paul Pu Liang; Ruslan Salakhutdinov; Louis-Philippe Morency; Masahito Ueda (NeurIPS, 2019)

Multiple Futures Prediction. - Yichuan Charlie Tang; Ruslan Salakhutdinov (NeurIPS, 2019)

XLNet: Generalized Autoregressive Pretraining for Language Understanding. - Zhilin Yang; Zihang Dai; Yiming Yang; Jaime G. Carbonell; Ruslan Salakhutdinov; Quoc V. Le (NeurIPS, 2019)

Mixtape: Breaking the Softmax Bottleneck Efficiently. - Zhilin Yang; Thang Luong; Ruslan Salakhutdinov; Quoc V. Le (NeurIPS, 2019)

The Omniglot Challenge: A 3-Year Progress Report. - Brenden M. Lake; Ruslan Salakhutdinov; Joshua B. Tenenbaum (CoRR, 2019)

Concurrent Meta Reinforcement Learning. - Emilio Parisotto; Soham Ghosh; Sai Bhargav Yalamanchi; Varsha Chinnaobireddy; Yuhuai Wu; Ruslan Salakhutdinov (CoRR, 2019)

The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors. - William H. Guss; Cayden Codel; Katja Hofmann; Brandon Houghton; Noburu Kuno; Stephanie Milani; Sharada P. Mohanty; Diego Perez Liebana; Ruslan Salakhutdinov; Nicholay Topin; Manuela Veloso; Phillip Wang (CoRR, 2019)

Efficient Exploration via State Marginal Matching. - Lisa Lee; Benjamin Eysenbach; Emilio Parisotto; Eric P. Xing; Sergey Levine; Ruslan Salakhutdinov (CoRR, 2019)

"My Way of Telling a Story": Persona based Grounded Story Generation. - Shrimai Prabhumoye; Khyathi Raghavi Chandu; Ruslan Salakhutdinov; Alan W. Black (CoRR, 2019)

LSMI-Sinkhorn: Semi-supervised Squared-Loss Mutual Information Estimation with Optimal Transport. - Yanbin Liu; Makoto Yamada; Yao-Hung Hubert Tsai; Tam Le; Ruslan Salakhutdinov; Yi Yang 001 (CoRR, 2019)

On Universal Approximation by Neural Networks with Uniform Guarantees on Approximation of Infinite Dimensional Maps. - William H. Guss; Ruslan Salakhutdinov (CoRR, 2019)

Enhanced Convolutional Neural Tangent Kernels. - Zhiyuan Li 005; Ruosong Wang; Dingli Yu; Simon S. Du; Wei Hu 014; Ruslan Salakhutdinov; Sanjeev Arora (CoRR, 2019)

Geometric Capsule Autoencoders for 3D Point Clouds. - Nitish Srivastava; Hanlin Goh; Ruslan Salakhutdinov (CoRR, 2019)

External vs. Internal: An Essay on Machine Learning Agents for Autonomous Database Management Systems. - Andrew Pavlo; Matthew Butrovich; Ananya Joshi 001; Lin Ma 006; Prashanth Menon; Dana Van Aken; Lisa Lee; Ruslan Salakhutdinov (IEEE Data Eng. Bull., 2019)

Towards Debiasing Sentence Representations. - Paul Pu Liang; Irene Mengze Li; Emily Zheng; Yao Chong Lim; Ruslan Salakhutdinov; Louis-Philippe Morency (ACL, 2020)

Politeness Transfer: A Tag and Generate Approach. - Aman Madaan; Amrith Setlur; Tanmay Parekh; Barnabás Póczos; Graham Neubig; Yiming Yang; Ruslan Salakhutdinov; Alan W. Black; Shrimai Prabhumoye (ACL, 2020)

Topological Sort for Sentence Ordering. - Shrimai Prabhumoye; Ruslan Salakhutdinov; Alan W. Black (ACL, 2020)

On Emergent Communication in Competitive Multi-Agent Teams. - Paul Pu Liang; Jeffrey Chen; Ruslan Salakhutdinov; Louis-Philippe Morency; Satwik Kottur (AAMAS, 2020)

Exploring Controllable Text Generation Techniques. - Shrimai Prabhumoye; Alan W. Black; Ruslan Salakhutdinov (COLING, 2020)

Neural Topological SLAM for Visual Navigation. - Devendra Singh Chaplot; Ruslan Salakhutdinov; Abhinav Gupta 001; Saurabh Gupta 001 (CVPR, 2020)

Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis. - Yao-Hung Hubert Tsai; Martin Ma; Muqiao Yang; Ruslan Salakhutdinov; Louis-Philippe Morency (EMNLP (1), 2020)

Complex Transformer: A Framework for Modeling Complex-Valued Sequence. - Muqiao Yang; Martin Q. Ma; Dongyu Li; Yao-Hung Hubert Tsai; Ruslan Salakhutdinov (ICASSP, 2020)

Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. - Sanjeev Arora; Simon S. Du; Zhiyuan Li 005; Ruslan Salakhutdinov; Ruosong Wang; Dingli Yu (ICLR, 2020)

Learning To Explore Using Active Neural SLAM. - Devendra Singh Chaplot; Dhiraj Gandhi; Saurabh Gupta 001; Abhinav Gupta 001; Ruslan Salakhutdinov (ICLR, 2020)

Differentiable Reasoning over a Virtual Knowledge Base. - Bhuwan Dhingra; Manzil Zaheer; Vidhisha Balachandran; Graham Neubig; Ruslan Salakhutdinov; William W. Cohen (ICLR, 2020)

Capsules with Inverted Dot-Product Attention Routing. - Yao-Hung Hubert Tsai; Nitish Srivastava; Hanlin Goh; Ruslan Salakhutdinov (ICLR, 2020)

Embodied Multimodal Multitask Learning. - Devendra Singh Chaplot; Lisa Lee; Ruslan Salakhutdinov; Devi Parikh; Dhruv Batra (IJCAI, 2020)

Object Goal Navigation using Goal-Oriented Semantic Exploration. - Devendra Singh Chaplot; Dhiraj Gandhi; Abhinav Gupta 001; Ruslan Salakhutdinov (NeurIPS, 2020)

Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement. - Ben Eysenbach; Xinyang Geng; Sergey Levine; Ruslan Salakhutdinov (NeurIPS, 2020)

Weakly-Supervised Reinforcement Learning for Controllable Behavior. - Lisa Lee; Ben Eysenbach; Ruslan Salakhutdinov; Shixiang Shane Gu; Chelsea Finn (NeurIPS, 2020)

Neural Methods for Point-wise Dependency Estimation. - Yao-Hung Hubert Tsai; Han Zhao 002; Makoto Yamada; Louis-Philippe Morency; Ruslan Salakhutdinov (NeurIPS, 2020)

On Reward-Free Reinforcement Learning with Linear Function Approximation. - Ruosong Wang; Simon S. Du; Lin F. Yang; Ruslan Salakhutdinov (NeurIPS, 2020)

Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension. - Ruosong Wang; Ruslan Salakhutdinov; Lin F. Yang (NeurIPS, 2020)

Planning with General Objective Functions: Going Beyond Total Rewards. - Ruosong Wang; Peilin Zhong; Simon S. Du; Ruslan Salakhutdinov; Lin F. Yang (NeurIPS, 2020)

A Closer Look at Accuracy vs. Robustness. - Yao-Yuan Yang; Cyrus Rashtchian; Hongyang Zhang 001; Ruslan Salakhutdinov; Kamalika Chaudhuri (NeurIPS, 2020)

Think Locally, Act Globally: Federated Learning with Local and Global Representations. - Paul Pu Liang; Terrance Liu; Ziyin Liu; Ruslan Salakhutdinov; Louis-Philippe Morency (CoRR, 2020)

Learning Not to Learn in the Presence of Noisy Labels. - Ziyin Liu; Blair Chen; Ru Wang; Paul Pu Liang; Ruslan Salakhutdinov; Louis-Philippe Morency; Masahito Ueda (CoRR, 2020)

Adversarial Robustness Through Local Lipschitzness. - Yao-Yuan Yang; Cyrus Rashtchian; Hongyang Zhang 001; Ruslan Salakhutdinov; Kamalika Chaudhuri (CoRR, 2020)

Interpretable Multimodal Routing for Human Multimodal Language. - Yao-Hung Hubert Tsai; Martin Q. Ma; Muqiao Yang; Ruslan Salakhutdinov; Louis-Philippe Morency (CoRR, 2020)

Guaranteeing Reproducibility in Deep Learning Competitions. - Brandon Houghton; Stephanie Milani; Nicholay Topin; William H. Guss; Katja Hofmann; Diego Perez Liebana; Manuela Veloso; Ruslan Salakhutdinov (CoRR, 2020)

Provably Efficient Reinforcement Learning with General Value Function Approximation. - Ruosong Wang; Ruslan Salakhutdinov; Lin F. Yang (CoRR, 2020)

Feature Robust Optimal Transport for High-dimensional Data. - Mathis Petrovich; Chao Liang; Yanbin Liu; Yao-Hung Hubert Tsai; Linchao Zhu; Yi Yang 001; Ruslan Salakhutdinov; Makoto Yamada (CoRR, 2020)

Demystifying Self-Supervised Learning: An Information-Theoretical Framework. - Yao-Hung Hubert Tsai; Yue Wu 001; Ruslan Salakhutdinov; Louis-Philippe Morency (CoRR, 2020)

Few-Shot Learning with Intra-Class Knowledge Transfer. - Vivek Roy; Yan Xu; Yu-Xiong Wang; Kris Kitani; Ruslan Salakhutdinov; Martial Hebert (CoRR, 2020)

Graph Adversarial Networks: Protecting Information against Adversarial Attacks. - Peiyuan Liao; Han Zhao 002; Keyulu Xu; Tommi S. Jaakkola; Geoffrey J. Gordon; Stefanie Jegelka; Ruslan Salakhutdinov (CoRR, 2020)

Planning with Submodular Objective Functions. - Ruosong Wang; Hanrui Zhang; Devendra Singh Chaplot; Denis Garagic; Ruslan Salakhutdinov (CoRR, 2020)

Unsupervised Domain Adaptation for Visual Navigation. - Shangda Li; Devendra Singh Chaplot; Yao-Hung Hubert Tsai; Yue Wu 001; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2020)

Close Category Generalization. - Yao-Yuan Yang; Cyrus Rashtchian; Ruslan Salakhutdinov; Kamalika Chaudhuri (CoRR, 2020)

Combining Programmable Potentials and Neural Networks for Materials Problems. - Ryan Mohr; Allan M. Avila; Soham Ghosh; Ananta Bhattarai; Muqiao Yang; Xintian Feng; Martin Head-Gordon; Ruslan Salakhutdinov; Maria Fonoberova; Igor Mezic (AAAI Spring Symposium: MLPS, 2021)

Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data. - Paul Pu Liang; Terrance Liu; Anna Cai; Michal Muszynski; Ryo Ishii; Nicholas B. Allen; Randy Auerbach; David Brent; Ruslan Salakhutdinov; Louis-Philippe Morency (ACL/IJCNLP (1), 2021)

Understanding the Tradeoffs in Client-side Privacy for Downstream Speech Tasks. - Peter Wu; Paul Pu Liang; Jiatong Shi; Ruslan Salakhutdinov; Shinji Watanabe 001; Louis-Philippe Morency (APSIPA ASC, 2021)

Hubert: How Much Can a Bad Teacher Benefit ASR Pre-Training? - Wei-Ning Hsu; Yao-Hung Hubert Tsai; Benjamin Bolte; Ruslan Salakhutdinov; Abdelrahman Mohamed (ICASSP, 2021)

Learning to Hallucinate Examples from Extrinsic and Intrinsic Supervision. - Liangke Gui; Adrien Bardes; Ruslan Salakhutdinov; Alexander Hauptmann 001; Martial Hebert; Yu-Xiong Wang (ICCV, 2021)

Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. - Benjamin Eysenbach; Shreyas Chaudhari; Swapnil Asawa; Sergey Levine; Ruslan Salakhutdinov (ICLR, 2021)

C-Learning: Learning to Achieve Goals via Recursive Classification. - Benjamin Eysenbach; Ruslan Salakhutdinov; Sergey Levine (ICLR, 2021)

Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation. - Emilio Parisotto; Ruslan Salakhutdinov (ICLR, 2021)

Self-supervised Learning from a Multi-view Perspective. - Yao-Hung Hubert Tsai; Yue Wu 001; Ruslan Salakhutdinov; Louis-Philippe Morency (ICLR, 2021)

Self-supervised Representation Learning with Relative Predictive Coding. - Yao-Hung Hubert Tsai; Martin Q. Ma; Muqiao Yang; Han Zhao 002; Louis-Philippe Morency; Ruslan Salakhutdinov (ICLR, 2021)

From Differentiable Reasoning to Self-supervised Embodied Active Learning. - Russ Salakhutdinov (ICMI, 2021)

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. - Yue Wu 001; Shuangfei Zhai; Nitish Srivastava; Joshua M. Susskind; Jian Zhang 050; Ruslan Salakhutdinov; Hanlin Goh (ICML, 2021)

On Proximal Policy Optimization's Heavy-tailed Gradients. - Saurabh Garg; Joshua Zhanson; Emilio Parisotto; Adarsh Prasad; J. Zico Kolter; Zachary C. Lipton; Sivaraman Balakrishnan; Ruslan Salakhutdinov; Pradeep Ravikumar (ICML, 2021)

Towards Understanding and Mitigating Social Biases in Language Models. - Paul Pu Liang; Chiyu Wu; Louis-Philippe Morency; Ruslan Salakhutdinov (ICML, 2021)

Information Obfuscation of Graph Neural Networks. - Peiyuan Liao; Han Zhao 002; Keyulu Xu; Tommi S. Jaakkola; Geoffrey J. Gordon; Stefanie Jegelka; Ruslan Salakhutdinov (ICML, 2021)

Reasoning Over Virtual Knowledge Bases With Open Predicate Relations. - Haitian Sun; Patrick Verga; Bhuwan Dhingra; Ruslan Salakhutdinov; William W. Cohen (ICML, 2021)

Instabilities of Offline RL with Pre-Trained Neural Representation. - Ruosong Wang; Yifan Wu; Ruslan Salakhutdinov; Sham M. Kakade (ICML, 2021)

Multimodal Speech Summarization Through Semantic Concept Learning. - Shruti Palaskar; Ruslan Salakhutdinov; Alan W. Black; Florian Metze (Interspeech, 2021)

Cross-Modal Generalization: Learning in Low Resource Modalities via Meta-Alignment. - Paul Pu Liang; Peter Wu; Ziyin Liu; Louis-Philippe Morency; Ruslan Salakhutdinov (ACM Multimedia, 2021)

StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer. - Yiwei Lyu; Paul Pu Liang; Hai Pham; Eduard H. Hovy; Barnabás Póczos; Ruslan Salakhutdinov; Louis-Philippe Morency (NAACL-HLT, 2021)

Case Study: Deontological Ethics in NLP. - Shrimai Prabhumoye; Brendon Boldt; Ruslan Salakhutdinov; Alan W. Black (NAACL-HLT, 2021)

Focused Attention Improves Document-Grounded Generation. - Shrimai Prabhumoye; Kazuma Hashimoto; Yingbo Zhou; Alan W. Black; Ruslan Salakhutdinov (NAACL-HLT, 2021)

SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency. - Devendra Singh Chaplot; Murtaza Dalal; Saurabh Gupta 001; Jitendra Malik; Ruslan Salakhutdinov (NeurIPS, 2021)

Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives. - Murtaza Dalal; Deepak Pathak; Ruslan Salakhutdinov (NeurIPS, 2021)

Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification. - Ben Eysenbach; Sergey Levine; Ruslan Salakhutdinov (NeurIPS, 2021)

Robust Predictable Control. - Ben Eysenbach; Ruslan Salakhutdinov; Sergey Levine (NeurIPS, 2021)

MultiBench: Multiscale Benchmarks for Multimodal Representation Learning. - Paul Pu Liang; Yiwei Lyu; Xiang Fan; Zetian Wu; Yun Cheng; Jason Wu 001; Leslie Chen; Peter Wu; Michelle A. Lee; Yuke Zhu; Ruslan Salakhutdinov; Louis-Philippe Morency (NeurIPS Datasets and Benchmarks, 2021)

LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport. - Yanbin Liu; Makoto Yamada; Yao-Hung Hubert Tsai; Tam Le; Ruslan Salakhutdinov; Yi Yang 001 (ECML/PKDD (1), 2021)

Understanding the Tradeoffs in Client-Side Privacy for Speech Recognition. - Peter Wu; Paul Pu Liang; Ruslan Salakhutdinov; Louis-Philippe Morency (CoRR, 2021)

The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors. - William H. Guss; Mario Ynocente Castro; Sam Devlin; Brandon Houghton; Noboru Sean Kuno; Crissman Loomis; Stephanie Milani; Sharada P. Mohanty; Keisuke Nakata; Ruslan Salakhutdinov; John Schulman; Shinya Shiroshita; et al. (CoRR, 2021)

A Note on Connecting Barlow Twins with Negative-Sample-Free Contrastive Learning. - Yao-Hung Hubert Tsai; Shaojie Bai; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2021)

End-to-End Multihop Retrieval for Compositional Question Answering over Long Documents. - Haitian Sun; William W. Cohen; Ruslan Salakhutdinov (CoRR, 2021)

Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations. - Yao-Hung Hubert Tsai; Martin Q. Ma; Han Zhao 002; Kun Zhang 001; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2021)

Integrating Auxiliary Information in Self-supervised Learning. - Yao-Hung Hubert Tsai; Tianqin Li; Weixin Liu; Peiyuan Liao; Ruslan Salakhutdinov; Louis-Philippe Morency (CoRR, 2021)

Online Sub-Sampling for Reinforcement Learning with General Function Approximation. - Dingwen Kong; Ruslan Salakhutdinov; Ruosong Wang; Lin F. Yang (CoRR, 2021)

FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding. - Yanan Zheng; Jing Zhou; Yujie Qian; Ming Ding 004; Jian Li; Ruslan Salakhutdinov; Jie Tang 001; Sebastian Ruder; Zhilin Yang (CoRR, 2021)

Recurrent Model-Free RL is a Strong Baseline for Many POMDPs. - Tianwei Ni; Benjamin Eysenbach; Ruslan Salakhutdinov (CoRR, 2021)

HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units. - Wei-Ning Hsu; Benjamin Bolte; Yao-Hung Hubert Tsai; Kushal Lakhotia; Ruslan Salakhutdinov; Abdelrahman Mohamed (IEEE ACM Trans. Audio Speech Lang. Process., 2021)

ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. - Haitian Sun; William W. Cohen; Ruslan Salakhutdinov (ACL (1), 2022)

FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding. - Yanan Zheng; Jing Zhou; Yujie Qian; Ming Ding 004; Chonghua Liao; Li Jian; Ruslan Salakhutdinov; Jie Tang 001; Sebastian Ruder; Zhilin Yang (ACL (1), 2022)

DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations. - Yiwei Lyu; Paul Pu Liang; Zihao Deng; Ruslan Salakhutdinov; Louis-Philippe Morency (AIES, 2022)

PACS: A Dataset for Physical Audiovisual CommonSense Reasoning. - Samuel Yu; Peter Wu; Paul Pu Liang; Ruslan Salakhutdinov; Louis-Philippe Morency (ECCV (37), 2022)

Don't Copy the Teacher: Data and Model Challenges in Embodied Dialogue. - So Yeon Min; Hao Zhu 011; Ruslan Salakhutdinov; Yonatan Bisk (EMNLP, 2022)

Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis. - Yuxin Xiao; Paul Pu Liang; Umang Bhatt; Willie Neiswanger; Ruslan Salakhutdinov; Louis-Philippe Morency (EMNLP (Findings), 2022)

The Information Geometry of Unsupervised Reinforcement Learning. - Benjamin Eysenbach; Ruslan Salakhutdinov; Sergey Levine (ICLR, 2022)

FILM: Following Instructions in Language with Modular Methods. - So Yeon Min; Devendra Singh Chaplot; Pradeep Kumar Ravikumar; Yonatan Bisk; Ruslan Salakhutdinov (ICLR, 2022)

Learning Weakly-supervised Contrastive Representations. - Yao-Hung Hubert Tsai; Tianqin Li; Weixin Liu; Peiyuan Liao; Ruslan Salakhutdinov; Louis-Philippe Morency (ICLR, 2022)

Conditional Contrastive Learning with Kernel. - Yao-Hung Hubert Tsai; Tianqin Li; Martin Q. Ma; Han Zhao 002; Kun Zhang 001; Louis-Philippe Morency; Ruslan Salakhutdinov (ICLR, 2022)

C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. - Tianjun Zhang; Benjamin Eysenbach; Ruslan Salakhutdinov; Sergey Levine; Joseph E. Gonzalez (ICLR, 2022)

Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs. - Tianwei Ni; Benjamin Eysenbach; Ruslan Salakhutdinov (ICML, 2022)

Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. - Benjamin Eysenbach; Alexander Khazatsky; Sergey Levine; Ruslan Salakhutdinov (NeurIPS, 2022)

Imitating Past Successes can be Very Suboptimal. - Benjamin Eysenbach; Soumith Udatha; Russ Salakhutdinov; Sergey Levine (NeurIPS, 2022)

Contrastive Learning as Goal-Conditioned Reinforcement Learning. - Benjamin Eysenbach; Tianjun Zhang; Sergey Levine; Ruslan Salakhutdinov (NeurIPS, 2022)

Paraphrasing Is All You Need for Novel Object Captioning. - Cheng-Fu Yang; Yao-Hung Hubert Tsai; Wan-Cyuan Fan; Russ Salakhutdinov; Louis-Philippe Morency; Frank Wang (NeurIPS, 2022)

Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks. - Minji Yoon; John Palowitch; Dustin Zelle; Ziniu Hu; Ruslan Salakhutdinov; Bryan Perozzi (NeurIPS, 2022)

Feature-Robust Optimal Transport for High-Dimensional Data. - Mathis Petrovich; Chao Liang; Ryoma Sato; Yanbin Liu; Yao-Hung Hubert Tsai; Linchao Zhu; Yi Yang 001; Ruslan Salakhutdinov; Makoto Yamada (ECML/PKDD (5), 2022)

HighMMT: Towards Modality and Task Generalization for High-Modality Representation Learning. - Paul Pu Liang; Yiwei Lyu; Xiang Fan; Shentong Mo; Dani Yogatama; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2022)

Zero-shot Domain Adaptation of Heterogeneous Graphs via Knowledge Transfer Networks. - Minji Yoon; John Palowitch; Dustin Zelle; Ziniu Hu; Ruslan Salakhutdinov; Bryan Perozzi (CoRR, 2022)

Reasoning over Logically Interacted Conditions for Question Answering. - Haitian Sun; William W. Cohen; Ruslan Salakhutdinov (CoRR, 2022)

A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search. - Brandon Trabucco; Gunnar A. Sigurdsson; Robinson Piramuthu; Gaurav S. Sukhatme; Ruslan Salakhutdinov (CoRR, 2022)

MultiViz: An Analysis Benchmark for Visualizing and Understanding Multimodal Models. - Paul Pu Liang; Yiwei Lyu; Gunjan Chhablani; Nihal Jain; Zihao Deng; Xingbo Wang 001; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2022)

Scalable Privacy-enhanced Benchmark Graph Generative Model for Graph Convolutional Networks. - Minji Yoon; Yue Wu 001; John Palowitch; Bryan Perozzi; Ruslan Salakhutdinov (CoRR, 2022)

Paraphrasing Is All You Need for Novel Object Captioning. - Cheng-Fu Yang; Yao-Hung Hubert Tsai; Wan-Cyuan Fan; Ruslan Salakhutdinov; Louis-Philippe Morency; Yu-Chiang Frank Wang (CoRR, 2022)

Object Goal Navigation with End-to-End Self-Supervision. - So Yeon Min; Yao-Hung Hubert Tsai; Wei Ding; Ali Farhadi; Ruslan Salakhutdinov; Yonatan Bisk; Jian Zhang 050 (CoRR, 2022)

Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control. - Xiang Fan; Yiwei Lyu; Paul Pu Liang; Ruslan Salakhutdinov; Louis-Philippe Morency (ACL (Findings), 2023)

Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment. - Rohan Pandey; Rulin Shao; Paul Pu Liang; Ruslan Salakhutdinov; Louis-Philippe Morency (ACL (1), 2023)

MultiViz: Towards User-Centric Visualizations and Interpretations of Multimodal Models. - Paul Pu Liang; Yiwei Lyu; Gunjan Chhablani; Nihal Jain; Zihao Deng; Xingbo Wang 001; Louis-Philippe Morency; Ruslan Salakhutdinov (CHI Extended Abstracts, 2023)

Imitating Task and Motion Planning with Visuomotor Transformers. - Murtaza Dalal; Ajay Mandlekar; Caelan Reed Garrett; Ankur Handa; Ruslan Salakhutdinov; Dieter Fox (CoRL, 2023)

Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. - Raj Ghugare; Homanga Bharadhwaj; Benjamin Eysenbach; Sergey Levine; Russ Salakhutdinov (ICLR, 2023)

MultiViz: Towards Visualizing and Understanding Multimodal Models. - Paul Pu Liang; Yiwei Lyu; Gunjan Chhablani; Nihal Jain; Zihao Deng; Xingbo Wang 001; Louis-Philippe Morency; Ruslan Salakhutdinov (ICLR, 2023)

Scenario-based Question Answering with Interacting Contextual Properties. - Haitian Sun; William W. Cohen; Ruslan Salakhutdinov (ICLR, 2023)

A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search. - Brandon Trabucco; Gunnar A. Sigurdsson; Robinson Piramuthu; Gaurav S. Sukhatme; Ruslan Salakhutdinov (ICLR, 2023)

Multimodal Fusion Interactions: A Study of Human and Automatic Quantification. - Paul Pu Liang; Yun Cheng; Ruslan Salakhutdinov; Louis-Philippe Morency (ICMI, 2023)

A Connection between One-Step RL and Critic Regularization in Reinforcement Learning. - Benjamin Eysenbach; Matthieu Geist; Sergey Levine; Ruslan Salakhutdinov (ICML, 2023)

Grounding Language Models to Images for Multimodal Inputs and Outputs. - Jing Yu Koh; Ruslan Salakhutdinov; Daniel Fried (ICML, 2023)

Graph Generative Model for Benchmarking Graph Neural Networks. - Minji Yoon; Yue Wu 001; John Palowitch; Bryan Perozzi; Russ Salakhutdinov (ICML, 2023)

Self-Supervised Object Goal Navigation with In-Situ Finetuning. - So Yeon Min; Yao-Hung Hubert Tsai; Wei Ding; Ali Farhadi; Ruslan Salakhutdinov; Yonatan Bisk; Jian Zhang 050 (IROS, 2023)

Contrastive Example-Based Control. - Kyle Beltran Hatch; Benjamin Eysenbach; Rafael Rafailov; Tianhe Yu; Ruslan Salakhutdinov; Sergey Levine; Chelsea Finn (L4DC, 2023)

Generating Images with Multimodal Language Models. - Jing Yu Koh; Daniel Fried; Russ Salakhutdinov (NeurIPS, 2023)

Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework. - Paul Pu Liang; Yun Cheng; Xiang Fan; Chun Kai Ling; Suzanne Nie; Richard J. Chen; Zihao Deng; Nicholas B. Allen; Randy Auerbach; Faisal Mahmood; Russ Salakhutdinov; Louis-Philippe Morency (NeurIPS, 2023)

Factorized Contrastive Learning: Going Beyond Multi-view Redundancy. - Paul Pu Liang; Zihao Deng; Martin Q. Ma; James Y. Zou; Louis-Philippe Morency; Ruslan Salakhutdinov (NeurIPS, 2023)

SPRING: Studying Papers and Reasoning to play Games. - Yue Wu; So Yeon Min; Shrimai Prabhumoye; Yonatan Bisk; Russ Salakhutdinov; Amos Azaria; Tom M. Mitchell; Yuanzhi Li (NeurIPS, 2023)

Grounding Language Models to Images for Multimodal Generation. - Jing Yu Koh; Ruslan Salakhutdinov; Daniel Fried (CoRR, 2023)

Effective Data Augmentation With Diffusion Models. - Brandon Trabucco; Kyle Doherty; Max Gurinas; Ruslan Salakhutdinov (CoRR, 2023)

Quantifying & Modeling Feature Interactions: An Information Decomposition Framework. - Paul Pu Liang; Yun Cheng; Xiang Fan; Chun Kai Ling; Suzanne Nie; Richard J. Chen; Zihao Deng; Faisal Mahmood; Ruslan Salakhutdinov; Louis-Philippe Morency (CoRR, 2023)

Plan, Eliminate, and Track - Language Models are Good Teachers for Embodied Agents. - Yue Wu; So Yeon Min; Yonatan Bisk; Ruslan Salakhutdinov; Amos Azaria; Yuanzhi Li; Tom M. Mitchell; Shrimai Prabhumoye (CoRR, 2023)

SPRING: GPT-4 Out-performs RL Algorithms by Studying Papers and Reasoning. - Yue Wu; Shrimai Prabhumoye; So Yeon Min; Yonatan Bisk; Ruslan Salakhutdinov; Amos Azaria; Tom M. Mitchell; Yuanzhi Li (CoRR, 2023)

Stabilizing Contrastive RL: Techniques for Offline Goal Reaching. - Chongyi Zheng; Benjamin Eysenbach; Homer Walke; Patrick Yin; Kuan Fang; Ruslan Salakhutdinov; Sergey Levine (CoRR, 2023)

Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications. - Paul Pu Liang; Chun Kai Ling; Yun Cheng; Alex Obolenskiy; Yudong Liu; Rohan Pandey; Alex Wilf; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2023)

Factorized Contrastive Learning: Going Beyond Multi-view Redundancy. - Paul Pu Liang; Zihao Deng; Martin Ma; James Zou; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2023)

Localized Text-to-Image Generation for Free via Cross Attention Control. - Yutong He; Ruslan Salakhutdinov; J. Zico Kolter (CoRR, 2023)

MultiZoo & MultiBench: A Standardized Toolkit for Multimodal Deep Learning. - Paul Pu Liang; Yiwei Lyu; Xiang Fan; Arav Agarwal; Yun Cheng; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2023)

A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning. - Benjamin Eysenbach; Matthieu Geist; Sergey Levine; Ruslan Salakhutdinov (CoRR, 2023)

Answering Ambiguous Questions with a Database of Questions, Answers, and Revisions. - Haitian Sun; William W. Cohen; Ruslan Salakhutdinov (CoRR, 2023)

Confronting Reward Model Overoptimization with Constrained RLHF. - Ted Moskovitz; Aaditya K. Singh; DJ Strouse; Tuomas Sandholm; Ruslan Salakhutdinov; Anca D. Dragan; Stephen McAleer (CoRR, 2023)

Multimodal Graph Learning for Generative Tasks. - Minji Yoon; Jing Yu Koh; Bryan Hooi; Ruslan Salakhutdinov (CoRR, 2023)

Contrastive Difference Predictive Coding. - Chongyi Zheng; Ruslan Salakhutdinov; Benjamin Eysenbach (CoRR, 2023)

MultiIoT: Towards Large-scale Multisensory Learning for the Internet of Things. - Shentong Mo; Paul Pu Liang; Russ Salakhutdinov; Louis-Philippe Morency (CoRR, 2023)

MMOE: Mixture of Multimodal Interaction Experts. - Haofei Yu; Paul Pu Liang; Ruslan Salakhutdinov; Louis-Philippe Morency (CoRR, 2023)

Manifold Preserving Guided Diffusion. - Yutong He; Naoki Murata; Chieh-Hsin Lai; Yuhta Takida; Toshimitsu Uesaka; Dongjun Kim; Wei-Hsiang Liao; Yuki Mitsufuji; J. Zico Kolter; Ruslan Salakhutdinov; Stefano Ermon (CoRR, 2023)

MultiZoo and MultiBench: A Standardized Toolkit for Multimodal Deep Learning. - Paul Pu Liang; Yiwei Lyu; Xiang Fan; Arav Agarwal; Yun Cheng; Louis-Philippe Morency; Ruslan Salakhutdinov (J. Mach. Learn. Res., 2023)

Probing Predictions on OOD Images via Nearest Categories. - Yao-Yuan Yang; Cyrus Rashtchian; Ruslan Salakhutdinov; Kamalika Chaudhuri (Trans. Mach. Learn. Res., 2023)

VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks. - Jing Yu Koh; Robert Lo; Lawrence Jang; Vikram Duvvur; Ming Chong Lim; Po-Yu Huang; Graham Neubig; Shuyan Zhou; Ruslan Salakhutdinov; Daniel Fried (CoRR, 2024)

OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web. - Raghav Kapoor; Yash Parag Butala; Melisa Russak; Jing Yu Koh; Kiran Kamble; Waseem AlShikh; Ruslan Salakhutdinov (CoRR, 2024)

Automatic Question-Answer Generation for Long-Tail Knowledge. - Rohan Kumar; Youngmin Kim; Sunitha Ravi; Haitian Sun; Christos Faloutsos; Ruslan Salakhutdinov; Minji Yoon (CoRR, 2024)

Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. - Benjamin Eysenbach; Vivek Myers; Ruslan Salakhutdinov; Sergey Levine (CoRR, 2024)

Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation. - Yutong He; Alexander Robey; Naoki Murata; Yiding Jiang; Joshua Williams; George J. Pappas; Hamed Hassani; Yuki Mitsufuji; Ruslan Salakhutdinov; J. Zico Kolter (CoRR, 2024)

AgentKit: Flow Engineering with Graphs, not Coding. - Yue Wu; Yewen Fan; So Yeon Min; Shrimai Prabhumoye; Stephen McAleer; Yonatan Bisk; Ruslan Salakhutdinov; Yuanzhi Li; Tom M. Mitchell (CoRR, 2024)

Stylus: Automatic Adapter Selection for Diffusion Models. - Michael Luo; Justin Wong; Brandon Trabucco; Yanping Huang; Joseph E. Gonzalez; Zhifeng Chen; Ruslan Salakhutdinov; Ion Stoica (CoRR, 2024)

Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks. - Murtaza Dalal; Tarun Chiruvolu; Devendra Singh Chaplot; Ruslan Salakhutdinov (CoRR, 2024)

Leafy Spurge Dataset: Real-world Weed Classification Within Aerial Drone Imagery. - Kyle Doherty; Max Gurinas; Erik Samsoe; Charles Casper; Beau Larkin; Philip Ramsey; Brandon Trabucco; Ruslan Salakhutdinov (CoRR, 2024)

Understanding Visual Concepts Across Models. - Brandon Trabucco; Max Gurinas; Kyle Doherty; Ruslan Salakhutdinov (CoRR, 2024)

Adversarial Attacks on Multimodal Agents. - Chen Henry Wu; Jing Yu Koh; Ruslan Salakhutdinov; Daniel Fried; Aditi Raghunathan (CoRR, 2024)