Jinwoo Shin

Orcid: 0000-0003-4313-4669

According to our database1, Jinwoo Shin authored at least 244 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

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On csauthors.net:

Bibliography

2024
Holistic Molecular Representation Learning via Multi-view Fragmentation.
Trans. Mach. Learn. Res., 2024

Tabular Transfer Learning via Prompting LLMs.
CoRR, 2024

Safeguard Text-to-Image Diffusion Models with Human Feedback Inversion.
CoRR, 2024

Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning.
CoRR, 2024

Aligning Large Language Models with Self-generated Preference Data.
CoRR, 2024

ReMoDetect: Reward Models Recognize Aligned LLM's Generations.
CoRR, 2024

Improving Diffusion Models for Virtual Try-on.
CoRR, 2024

Online Adaptation of Language Models with a Memory of Amortized Contexts.
CoRR, 2024

Direct Consistency Optimization for Compositional Text-to-Image Personalization.
CoRR, 2024

Few-Shot Anomaly Detection via Personalization.
IEEE Access, 2024

Data-Efficient Molecular Generation with Hierarchical Textual Inversion.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Visual Representation Learning with Stochastic Frame Prediction.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

DreamFlow: High-quality text-to-3D generation by Approximating Probability Flow.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Querying Easily Flip-flopped Samples for Deep Active Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Improving Diffusion Models for Authentic Virtual Try-on in the Wild.
Proceedings of the Computer Vision - ECCV 2024, 2024

Adversarial Robustification via Text-to-Image Diffusion Models.
Proceedings of the Computer Vision - ECCV 2024, 2024

Discovering and Mitigating Visual Biases Through Keyword Explanation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling.
Trans. Mach. Learn. Res., 2023

DAPPER: Label-Free Performance Estimation after Personalization for Heterogeneous Mobile Sensing.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2023

NeFL: Nested Federated Learning for Heterogeneous Clients.
CoRR, 2023

Towards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion Models.
CoRR, 2023

Collaborative Score Distillation for Consistent Visual Synthesis.
CoRR, 2023

S-CLIP: Semi-supervised Vision-Language Pre-training using Few Specialist Captions.
CoRR, 2023

Efficient Meta-Learning via Error-based Context Pruning for Implicit Neural Representations.
CoRR, 2023

Explaining Visual Biases as Words by Generating Captions.
CoRR, 2023

Deep Self-Supervised Diversity Promoting Learning on Hierarchical Hyperspheres for Regularization.
IEEE Access, 2023

Rethinking the Entropy of Instance in Adversarial Training.
Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

Learning Large-scale Neural Fields via Context Pruned Meta-Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Slimmed Asymmetrical Contrastive Learning and Cross Distillation for Lightweight Model Training.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Guide Your Agent with Adaptive Multimodal Rewards.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Collaborative Score Distillation for Consistent Visual Editing.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-scale Diffusion Denoised Smoothing.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mosaic: Extremely Low-resolution RFID Vision for Visually-anonymized Action Recognition.
Proceedings of the 22nd International Conference on Information Processing in Sensor Networks, 2023

Multi-View Masked World Models for Visual Robotic Manipulation.
Proceedings of the International Conference on Machine Learning, 2023

Modality-Agnostic Variational Compression of Implicit Neural Representations.
Proceedings of the International Conference on Machine Learning, 2023

Prefer to Classify: Improving Text Classifiers via Auxiliary Preference Learning.
Proceedings of the International Conference on Machine Learning, 2023

STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Guiding Energy-based Models via Contrastive Latent Variables.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Imitating Graph-Based Planning with Goal-Conditioned Policies.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Preference Transformer: Modeling Human Preferences using Transformers for RL.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

String-Based Molecule Generation Via Multi-Decoder VAE.
Proceedings of the IEEE International Conference on Acoustics, 2023

A Study on the Assistive System for Safe Elevator Get on of Wheelchair Users with Upper Limb Disability.
Proceedings of the International Conference on Electronics, Information, and Communication, 2023

IFSeg: Image-free Semantic Segmentation via Vision-Language Model.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Video Probabilistic Diffusion Models in Projected Latent Space.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Enhancing Multiple Reliability Measures via Nuisance-Extended Information Bottleneck.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

BiasAdv: Bias-Adversarial Augmentation for Model Debiasing.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

infoVerse: A Universal Framework for Dataset Characterization with Multidimensional Meta-information.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Confidence-Aware Training of Smoothed Classifiers for Certified Robustness.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Adapting to Unknown Conditions in Learning-Based Mobile Sensing.
IEEE Trans. Mob. Comput., 2022

OAMixer: Object-aware Mixing Layer for Vision Transformers.
CoRR, 2022

String-based Molecule Generation via Multi-decoder VAE.
CoRR, 2022

Robust Continual Test-time Adaptation: Instance-aware BN and Prediction-balanced Memory.
CoRR, 2022

Zero-shot Blind Image Denoising via Implicit Neural Representations.
CoRR, 2022

Meta-Learning with Self-Improving Momentum Target.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

RényiCL: Contrastive Representation Learning with Skew Rényi Divergence.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Scalable Neural Video Representations with Learnable Positional Features.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Time Is MattEr: Temporal Self-supervision for Video Transformers.
Proceedings of the International Conference on Machine Learning, 2022

Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022

TSPipe: Learn from Teacher Faster with Pipelines.
Proceedings of the International Conference on Machine Learning, 2022

Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Model-augmented Prioritized Experience Replay.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Spread Spurious Attribute: Improving Worst-group Accuracy with Spurious Attribute Estimation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

What Makes Better Augmentation Strategies? Augment Difficult but Not too Different.
Proceedings of the Tenth International Conference on Learning Representations, 2022

A Study on Window-based Path Driving through Identifying the Target Walking in an Ultrasonic Sensor-based Follow-up Collaborative Robot.
Proceedings of the International Conference on Electronics, Information, and Communication, 2022

OpenCoS: Contrastive Semi-supervised Learning for Handling Open-Set Unlabeled Data.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

K-centered Patch Sampling for Efficient Video Recognition.
Proceedings of the Computer Vision - ECCV 2022, 2022

Patch-level Representation Learning for Self-supervised Vision Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Contrastive Dual Gating: Learning Sparse Features With Contrastive Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Self-Supervised Dense Consistency Regularization for Image-to-Image Translation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Consistency Regularization for Adversarial Robustness.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
DAPPER: Performance Estimation of Domain Adaptation in Mobile Sensing.
CoRR, 2021

Abstract Reasoning via Logic-guided Generation.
CoRR, 2021

Consistency and Monotonicity Regularization for Neural Knowledge Tracing.
CoRR, 2021

Random Features for the Neural Tangent Kernel.
CoRR, 2021

Model-Augmented Q-learning.
CoRR, 2021

Field Experiment of Photonic Radar for Low-RCS Target Detection and High-Resolution Image Acquisition.
IEEE Access, 2021

Elastic Resource Sharing for Distributed Deep Learning.
Proceedings of the 18th USENIX Symposium on Networked Systems Design and Implementation, 2021

Scaling Neural Tangent Kernels via Sketching and Random Features.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

RoMA: Robust Model Adaptation for Offline Model-based Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Object-aware Contrastive Learning for Debiased Scene Representation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Meta-Learning Sparse Implicit Neural Representations.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Improving Transferability of Representations via Augmentation-Aware Self-Supervision.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

State Entropy Maximization with Random Encoders for Efficient Exploration.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning to Generate Noise for Multi-Attack Robustness.
Proceedings of the 38th International Conference on Machine Learning, 2021

Self-Improved Retrosynthetic Planning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Minimum Width for Universal Approximation.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning to Sample with Local and Global Contexts in Experience Replay Buffer.
Proceedings of the 9th International Conference on Learning Representations, 2021

i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Layer-adaptive Sparsity for the Magnitude-based Pruning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Training GANs with Stronger Augmentations via Contrastive Discriminator.
Proceedings of the 9th International Conference on Learning Representations, 2021

Co<sup>2</sup>L: Contrastive Continual Learning.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Quality-Agnostic Image Recognition via Invertible Decoder.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Provable Memorization via Deep Neural Networks using Sub-linear Parameters.
Proceedings of the Conference on Learning Theory, 2021

GTA: Graph Truncated Attention for Retrosynthesis.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

MASKER: Masked Keyword Regularization for Reliable Text Classification.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Dynamic Control for On-Demand Interference-Managed WLAN Infrastructures.
IEEE/ACM Trans. Netw., 2020

Information Source Finding in Networks: Querying With Budgets.
IEEE/ACM Trans. Netw., 2020

Unified statistical performance of FSO link due to the combined effect of weak turbulence and generalized pointing error with HD and IM/DD.
J. Commun. Networks, 2020

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning.
CoRR, 2020

i-Mix: A Strategy for Regularizing Contrastive Representation Learning.
CoRR, 2020

A Deeper Look at the Layerwise Sparsity of Magnitude-based Pruning.
CoRR, 2020

Learning from Failure: Training Debiased Classifier from Biased Classifier.
CoRR, 2020

Learning to Generate Noise for Robustness against Multiple Perturbations.
CoRR, 2020

QOPT: Optimistic Value Function Decentralization for Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2020

Freeze Discriminator: A Simple Baseline for Fine-tuning GANs.
CoRR, 2020

CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning from Failure: De-biasing Classifier from Biased Classifier.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Bounds for Risk-sensitive Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Consistency Regularization for Certified Robustness of Smoothed Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Time-Reversal Symmetric ODE Network.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Guiding Deep Molecular Optimization with Genetic Exploration.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adversarial Neural Pruning with Latent Vulnerability Suppression.
Proceedings of the 37th International Conference on Machine Learning, 2020

Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Self-supervised Label Augmentation via Input Transformations.
Proceedings of the 37th International Conference on Machine Learning, 2020

Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix.
Proceedings of the 37th International Conference on Machine Learning, 2020

Learning What to Defer for Maximum Independent Sets.
Proceedings of the 37th International Conference on Machine Learning, 2020

Lookahead: A Far-sighted Alternative of Magnitude-based Pruning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Platform-Agnostic Lightweight Deep Learning for Garbage Collection Scheduling in SSDs.
Proceedings of the 12th USENIX Workshop on Hot Topics in Storage and File Systems, 2020

Regularizing Class-Wise Predictions via Self-Knowledge Distillation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

M2m: Imbalanced Classification via Major-to-Minor Translation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

DiscFace: Minimum Discrepancy Learning for Deep Face Recognition.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019
Simulation-Based Distributed Coordination Maximization Over Networks.
IEEE Trans. Control. Netw. Syst., 2019

Information source localization with protector diffusion in networks.
J. Commun. Networks, 2019

Rethinking Data Augmentation: Self-Supervision and Self-Distillation.
CoRR, 2019

A Simple Randomization Technique for Generalization in Deep Reinforcement Learning.
CoRR, 2019

Bitcoin vs. Bitcoin Cash: Coexistence or Downfall of Bitcoin Cash?
Proceedings of the 2019 IEEE Symposium on Security and Privacy, 2019

MetaSense: few-shot adaptation to untrained conditions in deep mobile sensing.
Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 2019

Mining GOLD Samples for Conditional GANs.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Towards Condition-Independent Deep Mobile Sensing.
Proceedings of the 17th Annual International Conference on Mobile Systems, 2019

Spectral Approximate Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019

Robust Inference via Generative Classifiers for Handling Noisy Labels.
Proceedings of the 36th International Conference on Machine Learning, 2019

Training CNNs with Selective Allocation of Channels.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning What and Where to Transfer.
Proceedings of the 36th International Conference on Machine Learning, 2019

InstaGAN: Instance-aware Image-to-Image Translation.
Proceedings of the 7th International Conference on Learning Representations, 2019

A Study on the Activation of Femoral Prostheses: Focused on the Development of a Decision Tree based Gait Phase Identification Algorithm.
Proceedings of the 16th International Conference on Informatics in Control, 2019

Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Techniques for Improving the Reliability of Prosthesis Wearer Muscle Signals Using Pressure and EMG Sensors.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Incremental Learning with Unlabeled Data in the Wild.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Energy Efficient Power Allocation for Multi-User MIMO Downlink Systems with Statistical Delay Constraints.
Proceedings of the 2019 IEEE Conference on Standards for Communications and Networking, 2019

Iterative Bayesian Learning for Crowdsourced Regression.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Game Theoretic Perspective of Optimal CSMA.
IEEE Trans. Wirel. Commun., 2018

Optimal Inference in Crowdsourced Classification via Belief Propagation.
IEEE Trans. Inf. Theory, 2018

Maximum Weight Matching Using Odd-Sized Cycles: Max-Product Belief Propagation and Half-Integrality.
IEEE Trans. Inf. Theory, 2018

Multi-armed Bandit with Additional Observations.
Proc. ACM Meas. Anal. Comput. Syst., 2018

Anytime Neural Prediction via Slicing Networks Vertically.
CoRR, 2018

Optimizing Spectral Sums using Randomized Chebyshev Expansions.
CoRR, 2018

Neural Adaptive Content-aware Internet Video Delivery.
Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation, 2018

Learning to Specialize with Knowledge Distillation for Visual Question Answering.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Stochastic Chebyshev Gradient Descent for Spectral Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Bucket Renormalization for Approximate Inference.
Proceedings of the 35th International Conference on Machine Learning, 2018

Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples.
Proceedings of the 6th International Conference on Learning Representations, 2018

Hierarchical Novelty Detection for Visual Object Recognition.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Gauged Mini-Bucket Elimination for Approximate Inference.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Approximating Spectral Sums of Large-Scale Matrices using Stochastic Chebyshev Approximations.
SIAM J. Sci. Comput., 2017

Convergence and Correctness of Max-Product Belief Propagation for Linear Programming.
SIAM J. Discret. Math., 2017

Scheduling Using Interactive Optimization Oracles for Constrained Queueing Networks.
Math. Oper. Res., 2017

Contextual Multi-armed Bandits under Feature Uncertainty.
CoRR, 2017

Sequential Local Learning for Latent Graphical Models.
CoRR, 2017

Efficient Learning for Crowdsourced Regression.
CoRR, 2017

Simplified Stochastic Feedforward Neural Networks.
CoRR, 2017

Gauging Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Adiabatic Persistent Contrastive Divergence learning.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Incentivizing strategic users for social diffusion: Quantity or quality?
Proceedings of the 2017 IEEE Conference on Computer Communications, 2017

Rumor source detection under querying with untruthful answers.
Proceedings of the 2017 IEEE Conference on Computer Communications, 2017

Confident Multiple Choice Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Faster Greedy MAP Inference for Determinantal Point Processes.
Proceedings of the 34th International Conference on Machine Learning, 2017

On the Delay Scaling Laws of Cache Networks.
Proceedings of the 12th International Conference on Future Internet Technologies, 2017

Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Distributed Medium Access Over Time-Varying Channels.
IEEE/ACM Trans. Netw., 2016

Delay Optimal CSMA With Linear Virtual Channels Under a General Topology.
IEEE/ACM Trans. Netw., 2016

On Maximizing Diffusion Speed Over Social Networks With Strategic Users.
IEEE/ACM Trans. Netw., 2016

Breaking the Trapping Sets in LDPC Codes: Check Node Removal and Collaborative Decoding.
IEEE Trans. Commun., 2016

Approximating the Spectral Sums of Large-scale Matrices using Chebyshev Approximations.
CoRR, 2016

MCMC assisted by Belief Propagaion.
CoRR, 2016

Synthesis of MCMC and Belief Propagation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Distributed coordination maximization over networks: a stochastic approximation approach.
Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2016

Just-in-time WLANs: On-demand interference-managed WLAN infrastructures.
Proceedings of the 35th Annual IEEE International Conference on Computer Communications, 2016

Estimating the rumor source with anti-rumor in social networks.
Proceedings of the 24th IEEE International Conference on Network Protocols, 2016

Optimality of Belief Propagation for Crowdsourced Classification.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Impacts of Selfish Behaviors on the Scalability of Hybrid Client-Server and Peer-to-Peer Caching Systems.
IEEE/ACM Trans. Netw., 2015

CSMA Using the Bethe Approximation: Scheduling and Utility Maximization.
IEEE Trans. Inf. Theory, 2015

Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Minimum Weight Perfect Matching via Blossom Belief Propagation.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

On the progressive spread over strategic diffusion: Asymptotic and computation.
Proceedings of the 2015 IEEE Conference on Computer Communications, 2015

Large-scale log-determinant computation through stochastic Chebyshev expansions.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Practical message-passing framework for large-scale combinatorial optimization.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
The Complexity of Approximating a Bethe Equilibrium.
IEEE Trans. Inf. Theory, 2014

Near-Optimality in Covering Games by Exposing Global Information.
ACM Trans. Economics and Comput., 2014

Max-Product Belief Propagation for Linear Programming: Convergence and Correctness.
CoRR, 2014

Scheduling using interactive oracles: connection between iterative optimization and low-complexity scheduling.
Proceedings of the ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, 2014

On maximizing diffusion speed in social networks: impact of random seeding and clustering.
Proceedings of the ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, 2014

Provable per-link delay-optimal CSMA for general wireless network topology.
Proceedings of the 2014 IEEE Conference on Computer Communications, 2014

Distributed learning for utility maximization over CSMA-based wireless multihop networks.
Proceedings of the 2014 IEEE Conference on Computer Communications, 2014

Influence maximization over strategic diffusion in social networks.
Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014

2013
CSMA using Statistical Physics toward Throughput and Utility Optimal CSMA.
CoRR, 2013

Loop Calculus and Bootstrap-Belief Propagation for Perfect Matchings on Arbitrary Graphs.
CoRR, 2013

A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

CSMA over time-varying channels: optimality, uniqueness and limited backoff rate.
Proceedings of the Fourteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2013

CSMA using the Bethe approximation for utility maximization.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Belief Propagation for Linear Programming.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Hybrid client-server and peer-to-peer caching systems with selfish peers.
Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013

On the impact of global information on diffusion of innovations over social networks.
Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013

2012
Complexity of Bethe Approximation.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

From Local to Global Stability in Stochastic Processing Networks through Quadratic Lyapunov Functions
CoRR, 2012

DRAM Scheduling Policy for GPGPU Architectures Based on a Potential Function.
IEEE Comput. Archit. Lett., 2012

Optimal CSMA: A survey.
Proceedings of the IEEE International Conference on Communication Systems, 2012

Minimally invasive mechanism design: Distributed covering with carefully chosen advice.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

2011
Counting Independent Sets Using the Bethe Approximation.
SIAM J. Discret. Math., 2011

Near Optimality in Covering and Packing Games by Exposing Global Information
CoRR, 2011

Efficient Distributed Medium Access
CoRR, 2011

Medium Access Using Queues.
Proceedings of the IEEE 52nd Annual Symposium on Foundations of Computer Science, 2011

Improved Mixing Condition on the Grid for Counting and Sampling Independent Sets.
Proceedings of the IEEE 52nd Annual Symposium on Foundations of Computer Science, 2011

2010
Distributed averaging via lifted Markov chains.
IEEE Trans. Inf. Theory, 2010

Distributed Random Access Algorithm: Scheduling and Congestion Control.
IEEE Trans. Inf. Theory, 2010

Efficient Queue-based CSMA with Collisions
CoRR, 2010

Delay optimal queue-based CSMA.
Proceedings of the SIGMETRICS 2010, 2010

Dynamics in congestion games.
Proceedings of the SIGMETRICS 2010, 2010

2009
Randomized Scheduling Algorithm for Queueing Networks
CoRR, 2009

Distributed Random Access Algorithm: Scheduling and Congesion Control
CoRR, 2009

Network adiabatic theorem: an efficient randomized protocol for contention resolution.
Proceedings of the Eleventh International Joint Conference on Measurement and Modeling of Computer Systems, 2009


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