Mengdi Wang

Orcid: 0000-0002-2101-9507

According to our database1, Mengdi Wang authored at least 254 papers between 2011 and 2025.

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Bibliography

2025
An interface tracking method with triangle edge cuts.
J. Comput. Phys., 2025

2024
Efficient Reinforcement Learning With Impaired Observability: Learning to Act With Delayed and Missing State Observations.
IEEE Trans. Inf. Theory, October, 2024

Redefining the Game: MVAE-DFDPnet's Low-Dimensional Embeddings for Superior Drug-Protein Interaction Predictions.
IEEE J. Biomed. Health Informatics, July, 2024

Prototype equilibrium network with group emotional contagion for few-shot emotion recognition in conversation.
Int. J. Mach. Learn. Cybern., June, 2024

Teamwork Reinforcement Learning With Concave Utilities.
IEEE Trans. Mob. Comput., May, 2024

Boosting the Convergence of Reinforcement Learning-Based Auto-Pruning Using Historical Data.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2024

Compressive stress gradients direct mechanoregulation of anisotropic growth in the zebrafish jaw joint.
PLoS Comput. Biol., February, 2024

Author Correction: A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions.
Nat. Mac. Intell., 2024

A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions.
Nat. Mac. Intell., 2024

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

On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control.
J. Mach. Learn. Res., 2024

A Theoretical Perspective for Speculative Decoding Algorithm.
CoRR, 2024

Global Convergence in Training Large-Scale Transformers.
CoRR, 2024

FoldMark: Protecting Protein Generative Models with Watermarking.
CoRR, 2024

Fast Best-of-N Decoding via Speculative Rejection.
CoRR, 2024

TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling.
CoRR, 2024

Long Term Memory: The Foundation of AI Self-Evolution.
CoRR, 2024

A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement.
CoRR, 2024

COMET: Towards Partical W4A4KV4 LLMs Serving.
CoRR, 2024

Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow.
CoRR, 2024

IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation.
CoRR, 2024

AIME: AI System Optimization via Multiple LLM Evaluators.
CoRR, 2024

Latent Diffusion Models for Controllable RNA Sequence Generation.
CoRR, 2024

Relative-Translation Invariant Wasserstein Distance.
CoRR, 2024

Conversational Dueling Bandits in Generalized Linear Models.
CoRR, 2024

Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data.
CoRR, 2024

Natural language is not enough: Benchmarking multi-modal generative AI for Verilog generation.
CoRR, 2024

Contractual Reinforcement Learning: Pulling Arms with Invisible Hands.
CoRR, 2024

Provable Statistical Rates for Consistency Diffusion Models.
CoRR, 2024

SAIL: Self-Improving Efficient Online Alignment of Large Language Models.
CoRR, 2024

Self-Play with Adversarial Critic: Provable and Scalable Offline Alignment for Language Models.
CoRR, 2024

Transfer Q Star: Principled Decoding for LLM Alignment.
CoRR, 2024

SpecDec++: Boosting Speculative Decoding via Adaptive Candidate Lengths.
CoRR, 2024

AI Risk Management Should Incorporate Both Safety and Security.
CoRR, 2024

CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments.
CoRR, 2024

Gradient Guidance for Diffusion Models: An Optimization Perspective.
CoRR, 2024

An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization.
CoRR, 2024

Diffusion Model for Data-Driven Black-Box Optimization.
CoRR, 2024

Embodied LLM Agents Learn to Cooperate in Organized Teams.
CoRR, 2024

Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory.
CoRR, 2024

Offline Multitask Representation Learning for Reinforcement Learning.
CoRR, 2024

Regularized DeepIV with Model Selection.
CoRR, 2024

MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences.
CoRR, 2024

Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules.
CoRR, 2024

Optimization of Emergency Supply and Distribution of Fresh Agricultural Products Under Public Health Emergencies.
IEEE Access, 2024

Conversational Dueling Bandits in Generalized Linear Models.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

A Novel Structured Task Scheduling Approach in Satellite Edge Computing Environments.
Proceedings of the IEEE International Conference on Web Services, 2024

Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Theoretical insights for diffusion guidance: A case study for Gaussian mixture models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Information-Directed Pessimism for Offline Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

MaxMin-RLHF: Alignment with Diverse Human Preferences.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

Embedding Large Language Models into Extended Reality: Opportunities and Challenges for Inclusion, Engagement, and Privacy.
Proceedings of the ACM Conversational User Interfaces 2024, 2024

Chipletizer: Repartitioning SoCs for Cost-Effective Chiplet Integration.
Proceedings of the 29th Asia and South Pacific Design Automation Conference, 2024

Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Visual Adversarial Examples Jailbreak Aligned Large Language Models.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Primal-Dual First-Order Methods for Affinely Constrained Multi-block Saddle Point Problems.
SIAM J. Optim., June, 2023

1xN Pattern for Pruning Convolutional Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Knowledge Annotation for Intelligent Textbooks.
Technol. Knowl. Learn., March, 2023

Distributed privacy-preserving nested compressed sensing for multiclass data collection with identity authentication.
Signal Process., 2023

Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition.
J. Mach. Learn. Res., 2023

Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning.
J. Mach. Learn. Res., 2023

Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning?
CoRR, 2023

Sample Complexity of Preference-Based Nonparametric Off-Policy Evaluation with Deep Networks.
CoRR, 2023

Federated Multi-Level Optimization over Decentralized Networks.
CoRR, 2023

Deep Reinforcement Learning for Efficient and Fair Allocation of Health Care Resources.
CoRR, 2023

Aligning Agent Policy with Externalities: Reward Design via Bilevel RL.
CoRR, 2023

Actions Speak What You Want: Provably Sample-Efficient Reinforcement Learning of the Quantal Stackelberg Equilibrium from Strategic Feedbacks.
CoRR, 2023

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

Scaling In-Context Demonstrations with Structured Attention.
CoRR, 2023

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

Visual Adversarial Examples Jailbreak Large Language Models.
CoRR, 2023

Adversarial Attacks on Online Learning to Rank with Stochastic Click Models.
CoRR, 2023

Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism.
CoRR, 2023

Eye-tracked Virtual Reality: A Comprehensive Survey on Methods and Privacy Challenges.
CoRR, 2023

ChipGPT: How far are we from natural language hardware design.
CoRR, 2023

Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP.
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

STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Deep Reinforcement Learning for Cost-Effective Medical Diagnosis.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Representation Learning for Low-rank General-sum Markov Games.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment.
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

The Construction of Intelligent Grasping System Based on EEG.
Proceedings of the Intelligent Robotics and Applications - 16th International Conference, 2023

Hierarchical Privacy-Preserving and Communication-Efficient Compression via Compressed Sensing.
Proceedings of the Data Compression Conference, 2023

Layer-Puzzle: Allocating and Scheduling Multi-task on Multi-core NPUs by Using Layer Heterogeneity.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

Provable Benefits of Representational Transfer in Reinforcement Learning.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Byzantine-Robust Online and Offline Distributed Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Deep Learning Compiler Optimization on Multi-Chiplet Architecture.
Proceedings of the 5th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2023

2022
A clebsch method for free-surface vortical flow simulation.
ACM Trans. Graph., 2022

Hydrophobic and Hydrophilic Solid-Fluid Interaction.
ACM Trans. Graph., 2022

A moving eulerian-lagrangian particle method for thin film and foam simulation.
ACM Trans. Graph., 2022

Weight Optimization of the Induction Magnetometer at Low Frequency.
IEEE Trans. Instrum. Meas., 2022

An Improved Convolutional Capsule Network for Compound Fault Diagnosis of RV Reducers.
Sensors, 2022

Energy system digitization in the era of AI: A three-layered approach toward carbon neutrality.
Patterns, 2022

A novel vehicular task deployment method in hybrid MEC.
J. Cloud Comput., 2022

Learning Markov Models Via Low-Rank Optimization.
Oper. Res., 2022

Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP.
CoRR, 2022

Energy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutrality.
CoRR, 2022

Representation Learning for General-sum Low-rank Markov Games.
CoRR, 2022

Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization.
CoRR, 2022

Optimal Estimation of Off-Policy Policy Gradient via Double Fitted Iteration.
CoRR, 2022

Offline stochastic shortest path: Learning, evaluation and towards optimality.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Communication Efficient Distributed Learning for Kernelized Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Parameter-Efficient Sparsity for Large Language Models Fine-Tuning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory.
Proceedings of the International Conference on Machine Learning, 2022

Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach.
Proceedings of the International Conference on Machine Learning, 2022

Optimal Estimation of Policy Gradient via Double Fitted Iteration.
Proceedings of the International Conference on Machine Learning, 2022

Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Neural Bandits for Protein Sequence Optimization.
Proceedings of the 56th Annual Conference on Information Sciences and Systems, 2022

Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Thin-film smoothed particle hydrodynamics fluid.
ACM Trans. Graph., 2021

Cautious Reinforcement Learning via Distributional Risk in the Dual Domain.
IEEE J. Sel. Areas Inf. Theory, 2021

Voting-Based Multiagent Reinforcement Learning for Intelligent IoT.
IEEE Internet Things J., 2021

Low-Cost and Confidentiality-Preserving Multi-Image Compressed Acquisition and Separate Reconstruction for Internet of Multimedia Things.
IEEE Internet Things J., 2021

Optimal policy evaluation using kernel-based temporal difference methods.
CoRR, 2021

You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient.
CoRR, 2021

MARL with General Utilities via Decentralized Shadow Reward Actor-Critic.
CoRR, 2021

1×N Block Pattern for Network Sparsity.
CoRR, 2021

Bootstrapping Statistical Inference for Off-Policy Evaluation.
CoRR, 2021

Sneak Analysis Based on Energy Flow in Thermal Systems With Recirculation Structure.
IEEE Access, 2021

On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Good State and Action Representations via Tensor Decomposition.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Bootstrapping Fitted Q-Evaluation for Off-Policy Inference.
Proceedings of the 38th International Conference on Machine Learning, 2021

Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient.
Proceedings of the 38th International Conference on Machine Learning, 2021

Low Complexity Secure P-Tensor Product Compressed Sensing Reconstruction Outsourcing and Identity Authentication in Cloud.
Proceedings of the IEEE International Conference on Acoustics, 2021

MT-DLA: An Efficient Multi-Task Deep Learning Accelerator Design.
Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

Contrastive Multi-document Question Generation.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Privacy-Preserving Compressed Sensing for Image Simultaneous Compression-Encryption Applications.
Proceedings of the 31st Data Compression Conference, 2021

Network-on-Interposer Design for Agile Neural-Network Processor Chip Customization.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

Towards Compact CNNs via Collaborative Compression.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Intermittent Communications in Decentralized Shadow Reward Actor-Critic.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Beyond Cumulative Returns via Reinforcement Learning over State-Action Occupancy Measures.
Proceedings of the 2021 American Control Conference, 2021

Generalization Bounds for Stochastic Saddle Point Problems.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Online Sparse Reinforcement Learning.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Spectral State Compression of Markov Processes.
IEEE Trans. Inf. Theory, 2020

A Novel High-Capacity Data Hiding in Encrypted Images Based on Compressive Sensing Progressive Recovery.
IEEE Signal Process. Lett., 2020

Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of Markov Chains.
SIAM J. Matrix Anal. Appl., 2020

A Single Timescale Stochastic Approximation Method for Nested Stochastic Optimization.
SIAM J. Optim., 2020

Randomized Linear Programming Solves the Markov Decision Problem in Nearly Linear (Sometimes Sublinear) Time.
Math. Oper. Res., 2020

Low-cost and high-efficiency privacy-protection scheme for distributed compressive video sensing in wireless multimedia sensor networks.
J. Netw. Comput. Appl., 2020

Bridging Exploration and General Function Approximation in Reinforcement Learning: Provably Efficient Kernel and Neural Value Iterations.
CoRR, 2020

Concept Annotation for Intelligent Textbooks.
CoRR, 2020

Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation.
CoRR, 2020

Variational Policy Gradient Method for Reinforcement Learning with General Utilities.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generalized Leverage Score Sampling for Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

High-Dimensional Sparse Linear Bandits.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fast Training of Deep Learning Models over Multiple GPUs.
Proceedings of the Middleware '20: 21st International Middleware Conference, 2020

Model-Based Reinforcement Learning with Value-Targeted Regression.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

A Duality Approach for Regret Minimization in Average-Award Ergodic Markov Decision Processes.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound.
Proceedings of the 37th International Conference on Machine Learning, 2020

Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation.
Proceedings of the 37th International Conference on Machine Learning, 2020

Model-Based Reinforcement Learning with Value-Targeted Regression.
Proceedings of the 37th International Conference on Machine Learning, 2020

A Many-Core Accelerator Design for On-Chip Deep Reinforcement Learning.
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020

A History-Based Auto-Tuning Framework for Fast and High-Performance DNN Design on GPU.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient.
Proceedings of the 2020 American Control Conference, 2020

Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Sketching Transformed Matrices with Applications to Natural Language Processing.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Multilevel Stochastic Gradient Methods for Nested Composition Optimization.
SIAM J. Optim., 2019

Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach.
Math. Program., 2019

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

Approximation Hardness for A Class of Sparse Optimization Problems.
J. Mach. Learn. Res., 2019

Privacy-Aware Controllable Compressed Data Publishing Against Sparse Estimation Attack in IoT.
IEEE Internet Things J., 2019

Unsupervised Common Question Generation from Multiple Documents using Reinforced Contrastive Coordinator.
CoRR, 2019

Continuous Control with Contexts, Provably.
CoRR, 2019

Voting-Based Multi-Agent Reinforcement Learning.
CoRR, 2019

RL4health: Crowdsourcing Reinforcement Learning for Knee Replacement Pathway Optimization.
CoRR, 2019

Feature-Based Q-Learning for Two-Player Stochastic Games.
CoRR, 2019

Reinforcement Leaning in Feature Space: Matrix Bandit, Kernels, and Regret Bound.
CoRR, 2019

Sample-Optimal Parametric Q-Learning with Linear Transition Models.
CoRR, 2019

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

Learning low-dimensional state embeddings and metastable clusters from time series data.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

State Aggregation Learning from Markov Transition Data.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Smart Roles: Inferring Professional Roles in Email Networks.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Maximum Likelihood Tensor Decomposition of Markov Decision Process.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Characterizing Deep Learning Training Workloads on Alibaba-PAI.
Proceedings of the IEEE International Symposium on Workload Characterization, 2019

Sample-Optimal Parametric Q-Learning Using Linearly Additive Features.
Proceedings of the 36th International Conference on Machine Learning, 2019

A Novel Privacy-Preserving Data Gathering Scheme in WSN Based on Compressive Sensing and Embedding.
Proceedings of the 2019 IEEE International Conference on Communications, 2019

Learning to Control in Metric Space with Optimal Regret.
Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2018
Controllable high-capacity separable data hiding in encrypted images by compressive sensing and data pretreatment.
Multim. Tools Appl., 2018

Near-optimal stochastic approximation for online principal component estimation.
Math. Program., 2018

Crowd escape event detection based on Direction-Collectiveness Model.
KSII Trans. Internet Inf. Syst., 2018

Auxiliary learning for crowd counting via count-net.
Neurocomputing, 2018

Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks.
CoRR, 2018

A bird's-eye view on coherence, and a worm's-eye view on cohesion.
CoRR, 2018

Diffusion Approximations for Online Principal Component Estimation and Global Convergence.
CoRR, 2018

Improved Oracle Complexity for Stochastic Compositional Variance Reduced Gradient.
CoRR, 2018

Scalable Bilinear π Learning Using State and Action Features.
CoRR, 2018

State Compression of Markov Processes via Empirical Low-Rank Estimation.
CoRR, 2018

Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes.
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018

Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model.
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

Estimation of Markov Chain via Rank-constrained Likelihood.
Proceedings of the 35th International Conference on Machine Learning, 2018

Scalable Bilinear Learning Using State and Action Features.
Proceedings of the 35th International Conference on Machine Learning, 2018

A Practice to Search the Summit of a DEM Using Simulated Annealing Technique.
Proceedings of the 26th International Conference on Geoinformatics, 2018

Efficient Deep Learning Inference Based on Model Compression.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Vanishing Price of Decentralization in Large Coordinative Nonconvex Optimization.
SIAM J. Optim., 2017

Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions.
Math. Program., 2017

Feature Extraction for Hyperspectral Images Using Low-Rank Representation With Neighborhood Preserving Regularization.
IEEE Geosci. Remote. Sens. Lett., 2017

基于边缘检测和特征融合的自然场景文本定位 (Text Localization Based on Edge Detection and Features Fusion in Natural Scene).
计算机科学, 2017

Accelerating Stochastic Composition Optimization.
J. Mach. Learn. Res., 2017

Abnormal Event Detection in Wireless Sensor Networks Based on Multiattribute Correlation.
J. Electr. Comput. Eng., 2017

Deep Primal-Dual Reinforcement Learning: Accelerating Actor-Critic using Bellman Duality.
CoRR, 2017

Primal-Dual π Learning: Sample Complexity and Sublinear Run Time for Ergodic Markov Decision Problems.
CoRR, 2017

Dynamic Factorization and Partition of Complex Networks.
CoRR, 2017

Randomized Linear Programming Solves the Discounted Markov Decision Problem In Nearly-Linear Running Time.
CoRR, 2017

Lower Bound On the Computational Complexity of Discounted Markov Decision Problems.
CoRR, 2017

The Signals and Noise: Actionable Information in Improvised Social Media Channels During a Disaster.
Proceedings of the 2017 ACM on Web Science Conference, 2017

Comparison of Different Centrality Measures to Find Influential Nodes in Complex Networks.
Proceedings of the Security, Privacy, and Anonymity in Computation, Communication, and Storage, 2017

Diffusion Approximations for Online Principal Component Estimation and Global Convergence.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions.
Proceedings of the 34th International Conference on Machine Learning, 2017

LRR-based hyperspectral image restoration by exploiting the union structure of spectral space and with robust dictionary estimation.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

Unsupervised feature extraction for hyperspectral images using combined low rank representation and locally linear embedding.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Finite-sum Composition Optimization via Variance Reduced Gradient Descent.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Generating Chinese Calligraphy on Freeform Shapes.
Trans. Comput. Sci., 2016

Denoising of Hyperspectral Images Using Group Low-Rank Representation.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016

Stochastic First-Order Methods with Random Constraint Projection.
SIAM J. Optim., 2016

基于贝叶斯方法和变化表的恐怖行为预测算法 (Terrorism Prediction Based on Bayes Method and Change Table).
计算机科学, 2016

Stochastic Primal-Dual Methods and Sample Complexity of Reinforcement Learning.
CoRR, 2016

A stochastic compositional gradient method using Markov samples.
Proceedings of the Winter Simulation Conference, 2016

Link Prediction via Multi-hashing Framework.
Proceedings of the Social, Cultural, and Behavioral Modeling, 9th International Conference, 2016

TeleLink: Link Prediction in Social Network Based on Multiplex Cohesive Structures.
Proceedings of the Social, Cultural, and Behavioral Modeling, 9th International Conference, 2016

Hyperspectral Image Denoising Based on Subspace Low Rank Representation.
Proceedings of the Geo-Spatial Knowledge and Intelligence, 2016

An online primal-dual method for discounted Markov decision processes.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015
Incremental constraint projection methods for variational inequalities.
Math. Program., 2015

A Distributed Tracking Algorithm for Reconstruction of Graph Signals.
IEEE J. Sel. Top. Signal Process., 2015

Random Multi-Constraint Projection: Stochastic Gradient Methods for Convex Optimization with Many Constraints.
CoRR, 2015

Group-based hyperspectral image denoising using low rank representation.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Averaging random projection: A fast online solution for large-scale constrained stochastic optimization.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Modeling and Verifying Google File System.
Proceedings of the 16th IEEE International Symposium on High Assurance Systems Engineering, 2015

Writing Chinese Calligraphy on Arbitrary Surfaces.
Proceedings of the International Conference on Cyberworlds, 2015

2014
Stabilization of Stochastic Iterative Methods for Singular and Nearly Singular Linear Systems.
Math. Oper. Res., 2014

Formalizing Google File System.
Proceedings of the 20th IEEE Pacific Rim International Symposium on Dependable Computing, 2014

Multi-task nonconvex optimization with total budget constraint: A distributed algorithm using Monte Carlo estimates.
Proceedings of the 19th International Conference on Digital Signal Processing, 2014

Learning distributed jointly sparse systems by collaborative LMS.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Stochastic methods for large-scale linear problems, variational inequalities, and convex optimization.
PhD thesis, 2013

A DT-SVM Strategy for Stock Futures Prediction with Big Data.
Proceedings of the 16th IEEE International Conference on Computational Science and Engineering, 2013

2011
SketchSet: Creating Euler diagrams using pen or mouse.
Proceedings of the 2011 IEEE Symposium on Visual Languages and Human-Centric Computing, 2011


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