b'Gen Li'

research

∙ 09/05/2023

STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation

In Location-Based Services, Point-Of-Interest(POI) recommendation plays ...

0 Shaohua Liu, et al. ∙

research

∙ 08/09/2023

TRTM: Template-based Reconstruction and Target-oriented Manipulation of Crumpled Cloths

Precisely reconstructing and manipulating crumpled cloths is challenging...

0 Wenbo Wang, et al. ∙

research

∙ 07/05/2023

DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models

Image super-resolution (SR) with generative adversarial networks (GAN) h...

0 Liangbin Xie, et al. ∙

research

∙ 06/18/2023

Referenceless User Controllable Semantic Image Synthesis

Despite recent progress in semantic image synthesis, complete control ov...

0 Jonghyun Kim, et al. ∙

research

∙ 06/15/2023

Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models

Diffusion models, which convert noise into new data instances by learnin...

4 Gen Li, et al. ∙

research

∙ 05/30/2023

Dynamic Sparsity Is Channel-Level Sparsity Learner

Sparse training has received an upsurging interest in machine learning d...

1 Lu Yin, et al. ∙

research

∙ 05/30/2023

Sharp high-probability sample complexities for policy evaluation with linear function approximation

This paper is concerned with the problem of policy evaluation with linea...

0 Gen Li, et al. ∙

research

∙ 05/26/2023

The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model

This paper investigates model robustness in reinforcement learning (RL) ...

5 Laixi Shi, et al. ∙

research

∙ 05/24/2023

Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time

A crucial problem in reinforcement learning is learning the optimal poli...

0 Xiang Ji, et al. ∙

research

∙ 05/17/2023

Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning

This paper studies tabular reinforcement learning (RL) in the hybrid set...

1 Gen Li, et al. ∙

research

∙ 05/07/2023

Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization

LASSO regularization is a popular regression tool to enhance the predict...

0 Gen Li, et al. ∙

research

∙ 04/14/2023

Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning

This paper studies reward-agnostic exploration in reinforcement learning...

7 Gen Li, et al. ∙

research

∙ 03/16/2023

LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding

Humans excel at acquiring knowledge through observation. For example, we...

0 Gen Li, et al. ∙

research

∙ 02/07/2023

Approximate message passing from random initialization with applications to ℤ_2 synchronization

This paper is concerned with the problem of reconstructing an unknown ra...

0 Gen Li, et al. ∙

research

∙ 02/07/2023

OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer

Omnidirectional images (ODIs) have obtained lots of research interest fo...

0 Fanghua Yu, et al. ∙

research

∙ 01/30/2023

Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods

Efficient computation of the optimal transport distance between two dist...

1 Gen Li, et al. ∙

research

∙ 12/02/2022

Multi-Agent Reinforcement Learning with Reward Delays

This paper considers multi-agent reinforcement learning (MARL) where the...

0 Yuyang Zhang, et al. ∙

research

∙ 09/06/2022

Reconstructing Action-Conditioned Human-Object Interactions Using Commonsense Knowledge Priors

We present a method for inferring diverse 3D models of human-object inte...

4 Xi Wang, et al. ∙

research

∙ 08/22/2022

Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model

This paper studies multi-agent reinforcement learning in Markov games, w...

3 Gen Li, et al. ∙

research

∙ 08/05/2022

A Non-Asymptotic Framework for Approximate Message Passing in Spiked Models

Approximate message passing (AMP) emerges as an effective iterative para...

0 Gen Li, et al. ∙

research

∙ 07/28/2022

Real Image Restoration via Structure-preserving Complementarity Attention

Since convolutional neural networks perform well in learning generalizab...

0 Yuanfan Zhang, et al. ∙

research

∙ 07/20/2022

FaceFormer: Scale-aware Blind Face Restoration with Transformers

Blind face restoration usually encounters with diverse scale face inputs...

0 Aijin Li, et al. ∙

research

∙ 06/14/2022

AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos

This paper studies the problem of real-world video super-resolution (VSR...

0 Yanze Wu, et al. ∙

research

∙ 06/08/2022

Model-Based Reinforcement Learning Is Minimax-Optimal for Offline Zero-Sum Markov Games

This paper makes progress towards learning Nash equilibria in two-player...

4 Yuling Yan, et al. ∙

research

∙ 05/13/2022

VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder

Although generative facial prior and geometric prior have recently demon...

0 Yuchao Gu, et al. ∙

research

∙ 05/11/2022

Principal Amalgamation Analysis for Microbiome Data

In recent years microbiome studies have become increasingly prevalent an...

0 Yan Li, et al. ∙

research

∙ 04/11/2022

Settling the Sample Complexity of Model-Based Offline Reinforcement Learning

This paper is concerned with offline reinforcement learning (RL), which ...

3 Gen Li, et al. ∙

research

∙ 03/14/2022

The Efficacy of Pessimism in Asynchronous Q-Learning

This paper is concerned with the asynchronous form of Q-learning, which ...

3 Yuling Yan, et al. ∙

research

∙ 02/28/2022

Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity

Offline or batch reinforcement learning seeks to learn a near-optimal po...

6 Laixi Shi, et al. ∙

research

∙ 12/17/2021

SuperStyleNet: Deep Image Synthesis with Superpixel Based Style Encoder

Existing methods for image synthesis utilized a style encoder based on s...

11 Jonghyun Kim, et al. ∙

research

∙ 10/09/2021

Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning

Achieving sample efficiency in online episodic reinforcement learning (R...

5 Gen Li, et al. ∙

research

∙ 06/22/2021

The Rate of Convergence of Variation-Constrained Deep Neural Networks

Multi-layer feedforward networks have been used to approximate a wide ra...

0 Gen Li, et al. ∙

research

∙ 05/17/2021

Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting

Low-complexity models such as linear function representation play a pivo...

6 Gen Li, et al. ∙

research

∙ 04/07/2021

Minimax Estimation of Linear Functions of Eigenvectors in the Face of Small Eigen-Gaps

Eigenvector perturbation analysis plays a vital role in various statisti...

8 Gen Li, et al. ∙

research

∙ 04/05/2021

Adaptive Prototype Learning and Allocation for Few-Shot Segmentation

Prototype learning is extensively used for few-shot segmentation. Typica...

0 Gen Li, et al. ∙

research

∙ 02/22/2021

Softmax Policy Gradient Methods Can Take Exponential Time to Converge

The softmax policy gradient (PG) method, which performs gradient ascent ...

6 Gen Li, et al. ∙

research

∙ 02/12/2021

Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis

Q-learning, which seeks to learn the optimal Q-function of a Markov deci...

4 Gen Li, et al. ∙

research

∙ 11/11/2020

It's All Relative: New Regression Paradigm for Microbiome Compositional Data

Microbiome data are complex in nature, involving high dimensionality, co...

0 Gen Li, et al. ∙

research

∙ 10/26/2020

The More Data, the Better? Demystifying Deletion-Based Methods in Linear Regression with Missing Data

We compare two deletion-based methods for dealing with the problem of mi...

0 Tianchen Xu, et al. ∙

research

∙ 10/02/2020

The Efficacy of L_1 Regularization in Two-Layer Neural Networks

A crucial problem in neural networks is to select the most appropriate n...

0 Gen Li, et al. ∙

research

∙ 09/05/2020

Learning Topological Motion Primitives for Knot Planning

In this paper, we approach the challenging problem of motion planning fo...

0 Mengyuan Yan, et al. ∙

research

∙ 08/27/2020

Edge and Identity Preserving Network for Face Super-Resolution

Face super-resolution has become an indispensable part in security probl...

0 Jonghyun Kim, et al. ∙

research

∙ 06/04/2020

Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction

Asynchronous Q-learning aims to learn the optimal action-value function ...

11 Gen Li, et al. ∙

research

∙ 05/31/2020

Multivariate Log-Contrast Regression with Sub-Compositional Predictors: Testing the Association Between Preterm Infants' Gut Microbiome and Neurobehavioral Outcomes

The so-called gut-brain axis has stimulated extensive research on microb...

0 Xiaokang Liu, et al. ∙

research

∙ 05/26/2020

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model

We investigate the sample efficiency of reinforcement learning in a γ-di...

4 Gen Li, et al. ∙

research

∙ 11/11/2019

Nonconvex Low-Rank Symmetric Tensor Completion from Noisy Data

We study a noisy symmetric tensor completion problem of broad practical ...

0 Changxiao Cai, et al. ∙

research

∙ 10/26/2019

Zero-inflated Poisson Factor Model with Application to Microbiome Absolute Abundance Data

Dimension reduction of high-dimensional microbiome data facilitates subs...

0 Tianchen Xu, et al. ∙

research

∙ 10/09/2019

Subspace Estimation from Unbalanced and Incomplete Data Matrices: ℓ_2,∞ Statistical Guarantees

This paper is concerned with estimating the column space of an unknown l...

0 Changxiao Cai, et al. ∙

research

∙ 08/16/2019

Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training

We propose Unicoder-VL, a universal encoder that aims to learn joint rep...

7 Gen Li, et al. ∙

research

∙ 07/26/2019

DABNet: Depth-wise Asymmetric Bottleneck for Real-time Semantic Segmentation

As a pixel-level prediction task, semantic segmentation needs large comp...

5 Gen Li, et al. ∙

Gen Li

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