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09/05/2023
STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation
In Location-Based Services, Point-Of-Interest(POI) recommendation plays ...
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08/09/2023
TRTM: Template-based Reconstruction and Target-oriented Manipulation of Crumpled Cloths
Precisely reconstructing and manipulating crumpled cloths is challenging...
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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...
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06/18/2023
Referenceless User Controllable Semantic Image Synthesis
Despite recent progress in semantic image synthesis, complete control ov...
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06/15/2023
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models
Diffusion models, which convert noise into new data instances by learnin...
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05/30/2023
Dynamic Sparsity Is Channel-Level Sparsity Learner
Sparse training has received an upsurging interest in machine learning d...
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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...
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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) ...
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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...
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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...
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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...
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04/14/2023
Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning
This paper studies reward-agnostic exploration in reinforcement learning...
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03/16/2023
LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding
Humans excel at acquiring knowledge through observation. For example, we...
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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...
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02/07/2023
OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer
Omnidirectional images (ODIs) have obtained lots of research interest fo...
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01/30/2023
Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods
Efficient computation of the optimal transport distance between two dist...
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12/02/2022
Multi-Agent Reinforcement Learning with Reward Delays
This paper considers multi-agent reinforcement learning (MARL) where the...
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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...
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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...
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08/05/2022
A Non-Asymptotic Framework for Approximate Message Passing in Spiked Models
Approximate message passing (AMP) emerges as an effective iterative para...
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07/28/2022
Real Image Restoration via Structure-preserving Complementarity Attention
Since convolutional neural networks perform well in learning generalizab...
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07/20/2022
FaceFormer: Scale-aware Blind Face Restoration with Transformers
Blind face restoration usually encounters with diverse scale face inputs...
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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...
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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...
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05/13/2022
VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder
Although generative facial prior and geometric prior have recently demon...
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05/11/2022
Principal Amalgamation Analysis for Microbiome Data
In recent years microbiome studies have become increasingly prevalent an...
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04/11/2022
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning
This paper is concerned with offline reinforcement learning (RL), which ...
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03/14/2022
The Efficacy of Pessimism in Asynchronous Q-Learning
This paper is concerned with the asynchronous form of Q-learning, which ...
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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...
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12/17/2021
SuperStyleNet: Deep Image Synthesis with Superpixel Based Style Encoder
Existing methods for image synthesis utilized a style encoder based on s...
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10/09/2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning
Achieving sample efficiency in online episodic reinforcement learning (R...
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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...
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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...
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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...
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04/05/2021
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation
Prototype learning is extensively used for few-shot segmentation. Typica...
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02/22/2021
Softmax Policy Gradient Methods Can Take Exponential Time to Converge
The softmax policy gradient (PG) method, which performs gradient ascent ...
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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...
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11/11/2020
It's All Relative: New Regression Paradigm for Microbiome Compositional Data
Microbiome data are complex in nature, involving high dimensionality, co...
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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...
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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...
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09/05/2020
Learning Topological Motion Primitives for Knot Planning
In this paper, we approach the challenging problem of motion planning fo...
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08/27/2020
Edge and Identity Preserving Network for Face Super-Resolution
Face super-resolution has become an indispensable part in security probl...
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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 ...
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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...
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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...
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11/11/2019
Nonconvex Low-Rank Symmetric Tensor Completion from Noisy Data
We study a noisy symmetric tensor completion problem of broad practical ...
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10/26/2019
Zero-inflated Poisson Factor Model with Application to Microbiome Absolute Abundance Data
Dimension reduction of high-dimensional microbiome data facilitates subs...
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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...
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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...
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07/26/2019
