Tuo Zhao

Orcid: 0000-0002-4991-7851

According to our database1, Tuo Zhao authored at least 185 papers between 2005 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Homotopic policy mirror descent: policy convergence, algorithmic regularization, and improved sample complexity.
Math. Program., September, 2024

Learning explainable task-relevant state representation for model-free deep reinforcement learning.
Neural Networks, 2024

Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds.
J. Mach. Learn. Res., 2024

Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces.
J. Mach. Learn. Res., 2024

RNR: Teaching Large Language Models to Follow Roles and Rules.
CoRR, 2024

Model Tells Itself Where to Attend: Faithfulness Meets Automatic Attention Steering.
CoRR, 2024

Robust Reinforcement Learning from Corrupted Human Feedback.
CoRR, 2024

RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning.
CoRR, 2024

Adaptive Preference Scaling for Reinforcement Learning with Human Feedback.
CoRR, 2024

Stochastic Constrained Decentralized Optimization for Machine Learning with Fewer Data Oracles: a Gradient Sliding Approach.
CoRR, 2024

GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM.
CoRR, 2024

BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering.
CoRR, 2024

Trust in Digital Commerce: the Moderating Effect of Blockchain Teability Labels.
Proceedings of the 28th Pacific Asia Conference on Information Systems, 2024

To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Hybrid Deep Generative and Sequential Learning Approach for Stock Market Prediction.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024

BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Data Diversity Matters for Robust Instruction Tuning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
Block Policy Mirror Descent.
SIAM J. Optim., September, 2023

Pivotal Estimation of Linear Discriminant Analysis in High Dimensions.
J. Mach. Learn. Res., 2023

Data Diversity Matters for Robust Instruction Tuning.
CoRR, 2023

Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult.
CoRR, 2023

Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process with Uncertainty Quantification.
CoRR, 2023

Deep Reinforcement Learning from Hierarchical Weak Preference Feedback.
CoRR, 2023

Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems.
CoRR, 2023

Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks.
CoRR, 2023

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers.
CoRR, 2023

Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Module-wise Adaptive Distillation for Multimodality Foundation Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories.
Proceedings of the International Conference on Machine Learning, 2023

Less is More: Task-aware Layer-wise Distillation for Language Model Compression.
Proceedings of the International Conference on Machine Learning, 2023

LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation.
Proceedings of the International Conference on Machine Learning, 2023

SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process.
Proceedings of the International Conference on Machine Learning, 2023

Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data.
Proceedings of the International Conference on Machine Learning, 2023

Machine Learning Force Fields with Data Cost Aware Training.
Proceedings of the International Conference on Machine Learning, 2023

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Joint Estimation of DOA and Distance in Noisy Reverberant Conditions.
Proceedings of the IEEE International Conference on Acoustics, 2023

Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Reinforcement Learning for Adaptive Mesh Refinement.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites.
Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, 2023

2022
Modeling Speech Structure to Improve T-F Masks for Speech Enhancement and Recognition.
IEEE ACM Trans. Audio Speech Lang. Process., 2022

Understanding users' trust transfer mechanism in a blockchain-enabled platform: A mixed methods study.
Decis. Support Syst., 2022

Efficient Long Sequence Modeling via State Space Augmented Transformer.
CoRR, 2022

High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization.
CoRR, 2022

First-order Policy Optimization for Robust Markov Decision Process.
CoRR, 2022

DiP-GNN: Discriminative Pre-Training of Graph Neural Networks.
CoRR, 2022

Differentially Private Estimation of Hawkes Process.
CoRR, 2022

A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks.
CoRR, 2022

Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity.
CoRR, 2022

Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network.
CoRR, 2022

TDOA Estimation of Speech Source in Noisy Reverberant Environments.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Self-Training with Differentiable Teacher.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Adversarially Regularized Policy Learning Guided by Trajectory Optimization.
Proceedings of the Learning for Dynamics and Control Conference, 2022

Steering vector correction in MVDR beamformer for speech enhancement.
Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance.
Proceedings of the International Conference on Machine Learning, 2022

Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint.
Proceedings of the International Conference on Machine Learning, 2022

Taming Sparsely Activated Transformer with Stochastic Experts.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect.
Proceedings of the Tenth International Conference on Learning Representations, 2022

No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Spectrum Truncation Power Iteration for Agnostic Matrix Phase Retrieval.
IEEE Trans. Signal Process., 2021

Learning Generalizable Vision-Tactile Robotic Grasping Strategy for Deformable Objects via Transformer.
CoRR, 2021

Implicit Regularization of Bregman Proximal Point Algorithm and Mirror Descent on Separable Data.
CoRR, 2021

Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach.
CoRR, 2021

COUnty aggRegation mixup AuGmEntation (COURAGE) COVID-19 Prediction.
CoRR, 2021

Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach.
CoRR, 2021

Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

UNet++-Based Multi-Channel Speech Dereverberation and Distant Speech Recognition.
Proceedings of the 12th International Symposium on Chinese Spoken Language Processing, 2021

Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

How Important is the Train-Validation Split in Meta-Learning?
Proceedings of the 38th International Conference on Machine Learning, 2021

A Hypergradient Approach to Robust Regression without Correspondence.
Proceedings of the 9th International Conference on Learning Representations, 2021

Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

ARCH: Efficient Adversarial Regularized Training with Caching.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Token-wise Curriculum Learning for Neural Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Learning to Defend by Learning to Attack.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks.
CoRR, 2020

Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers.
CoRR, 2020

Deep Reinforcement Learning with Smooth Policy.
CoRR, 2020

Differentiable Top-k Operator with Optimal Transport.
CoRR, 2020

Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation.
CoRR, 2020

Spatial Resolution Enhancement of Remote Sensing Hyperspectral Images With Localized Spatial-Spectral Dictionary Pair.
IEEE Access, 2020

The Role of Mobile Social Application in Stimulating Learning Stickiness in Blended Learning.
Proceedings of the 24th Pacific Asia Conference on Information Systems, 2020

Differentiable Top-k with Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? - A Neural Tangent Kernel Perspective.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Towards Understanding Hierarchical Learning: Benefits of Neural Representations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Transformer Hawkes Process.
Proceedings of the 37th International Conference on Machine Learning, 2020

Deep Reinforcement Learning with Robust and Smooth Policy.
Proceedings of the 37th International Conference on Machine Learning, 2020

Implicit Bias of Gradient Descent based Adversarial Training on Separable Data.
Proceedings of the 8th International Conference on Learning Representations, 2020

On Computation and Generalization of Generative Adversarial Imitation Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

On Generalization Bounds of a Family of Recurrent Neural Networks.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization.
IEEE Trans. Inf. Theory, 2019

Misspecified nonconvex statistical optimization for sparse phase retrieval.
Math. Program., 2019

Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python.
J. Mach. Learn. Res., 2019

Towards Understanding the Importance of Noise in Training Neural Networks.
CoRR, 2019

Inductive Bias of Gradient Descent based Adversarial Training on Separable Data.
CoRR, 2019

Review wearable sensing system for gait recognition.
Clust. Comput., 2019

Online Factorization and Partition of Complex Networks by Random Walk.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Meta Learning with Relational Information for Short Sequences.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Towards Understanding the Importance of Shortcut Connections in Residual Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Toward Understanding the Importance of Noise in Training Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

On Scalable and Efficient Computation of Large Scale Optimal Transport.
Proceedings of the 36th International Conference on Machine Learning, 2019

On Computation and Generalization of Generative Adversarial Networks under Spectrum Control.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Defense by Learning to Attack.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
On Computation and Generalization of GANs with Spectrum Control.
CoRR, 2018

Learning to Defense by Learning to Attack.
CoRR, 2018

On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond.
CoRR, 2018

On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization.
CoRR, 2018

Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models.
CoRR, 2018

Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations.
CoRR, 2018

Provable Gaussian Embedding with One Observation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The Physical Systems Behind Optimization Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
An enhance excavation equipments classification algorithm based on acoustic spectrum dynamic feature.
Multidimens. Syst. Signal Process., 2017

On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization.
J. Mach. Learn. Res., 2017

Excavation equipment classification based on improved MFCC features and ELM.
Neurocomputing, 2017

Misspecified Nonconvex Statistical Optimization for Phase Retrieval.
CoRR, 2017

Deep Hyperspherical Learning.
CoRR, 2017

Dynamic Factorization and Partition of Complex Networks.
CoRR, 2017

Homotopy Parametric Simplex Method for Sparse Learning.
CoRR, 2017

On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions.
CoRR, 2017

Online Multiview Representation Learning: Dropping Convexity for Better Efficiency.
CoRR, 2017

Parametric Simplex Method for Sparse Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deep Hyperspherical Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

The Opensesame NIST 2016 Speaker Recognition Evaluation System.
Proceedings of the 18th Annual Conference of the International Speech Communication Association, 2017

Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability.
Proceedings of the 34th International Conference on Machine Learning, 2017

Hyperspectral and multispectral image fusion using local spatial-spectral dictionary pair.
Proceedings of the 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2017

2016
Ensemble Acoustic Modeling for CD-DNN-HMM Using Random Forests of Phonetic Decision Trees.
J. Signal Process. Syst., 2016

Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization.
CoRR, 2016

A First Order Free Lunch for SQRT-Lasso.
CoRR, 2016

NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Hyperspectral and multispectral image fusion using collaborative representation with local adaptive dictionary pair.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

Subpixel mapping of hyperspectral images based on collaborative representation.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning.
Proceedings of the 33nd International Conference on Machine Learning, 2016

An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Calibrated multivariate regression with application to neural semantic basis discovery.
J. Mach. Learn. Res., 2015

The flare package for high dimensional linear regression and precision matrix estimation in R.
J. Mach. Learn. Res., 2015

A Nonconvex Optimization Framework for Low Rank Matrix Estimation.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Time-frequency kernel-based CNN for speech recognition.
Proceedings of the 16th Annual Conference of the International Speech Communication Association, 2015

2014
Calibrated Precision Matrix Estimation for High-Dimensional Elliptical Distributions.
IEEE Trans. Inf. Theory, 2014

Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory.
CoRR, 2014

Accelerated Mini-batch Randomized Block Coordinate Descent Method.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Multivariate Regression with Calibration.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Building an ensemble of CD-DNN-HMM acoustic model using random forests of phonetic decision trees.
Proceedings of the 9th International Symposium on Chinese Spoken Language Processing, 2014

Multilevel sampling and aggregation for discriminative training.
Proceedings of the 9th International Symposium on Chinese Spoken Language Processing, 2014

2013
CODA: high dimensional copula discriminant analysis.
J. Mach. Learn. Res., 2013

Sparse Inverse Covariance Estimation with Calibration.
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

2012
The huge Package for High-dimensional Undirected Graph Estimation in R.
J. Mach. Learn. Res., 2012

Sparse Additive Machine.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2010
Projected gradient method for kernel discriminant nonnegative matrix factorization and the applications.
Signal Process., 2010

2009
Predicting RNA secondary structure based on the class information and Hopfield network.
Comput. Biol. Medicine, 2009

2008
Interest filter vs. interest operator: Face recognition using Fisher linear discriminant based on interest filter representation.
Pattern Recognit. Lett., 2008

2007
A Novel Null Space-Based Kernel Discriminant Analysis for Face Recognition.
Proceedings of the Advances in Biometrics, International Conference, 2007

2006
Feature selection for linear support vector machines.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Curve Mapping Based Illumination Adjustment for Face Detection.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2006

2005
Re-lighting and Compensation for Face Images.
Proceedings of the Computer Analysis of Images and Patterns, 11th International Conference, 2005


  Loading...