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06/06/2023
Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage
We investigate the role of projection heads, also known as projectors, w...
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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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05/18/2023
Conformalized matrix completion
Matrix completion aims to estimate missing entries in a data matrix, usi...
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05/09/2023
Multi-Teacher Knowledge Distillation For Text Image Machine Translation
Text image machine translation (TIMT) has been widely used in various re...
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05/09/2023
E2TIMT: Efficient and Effective Modal Adapter for Text Image Machine Translation
Text image machine translation (TIMT) aims to translate texts embedded i...
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02/02/2023
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
We propose , a preconditioned gradient descent method to tackle the low-...
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10/08/2022
Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task
End-to-end text image translation (TIT), which aims at translating the s...
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09/26/2022
O(T^-1) Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games
We prove that optimistic-follow-the-regularized-leader (OFTRL), together...
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07/12/2022
Optimal tuning-free convex relaxation for noisy matrix completion
This paper is concerned with noisy matrix completion–the problem of reco...
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06/18/2022
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent
An increasing number of data science and machine learning problems rely ...
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05/21/2022
Pessimism for Offline Linear Contextual Bandits using ℓ_p Confidence Sets
We present a family {π̂}_p≥ 1 of pessimistic learning rules for offline ...
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05/06/2022
Optimally tackling covariate shift in RKHS-based nonparametric regression
We study the covariate shift problem in the context of nonparametric reg...
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04/05/2022
Jump-Start Reinforcement Learning
Reinforcement learning (RL) provides a theoretical framework for continu...
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02/06/2022
A new similarity measure for covariate shift with applications to nonparametric regression
We study covariate shift in the context of nonparametric regression. We ...
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06/26/2021
TANet++: Triple Attention Network with Filtered Pointcloud on 3D Detection
TANet is one of state-of-the-art 3D object detection method on KITTI and...
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04/29/2021
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements
Tensors, which provide a powerful and flexible model for representing mu...
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03/22/2021
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism
Offline (or batch) reinforcement learning (RL) algorithms seek to learn ...
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01/19/2021
Minimax Off-Policy Evaluation for Multi-Armed Bandits
We study the problem of off-policy evaluation in the multi-armed bandit ...
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01/13/2021
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing
Low-rank matrix estimation plays a central role in various applications ...
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12/15/2020
Spectral Methods for Data Science: A Statistical Perspective
Spectral methods have emerged as a simple yet surprisingly effective app...
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10/26/2020
Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number
Many problems in data science can be treated as estimating a low-rank ma...
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09/23/2020
Learning Mixtures of Low-Rank Models
We study the problem of learning mixtures of low-rank models, i.e. recon...
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05/18/2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent
Low-rank matrix estimation is a canonical problem that finds numerous ap...
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01/15/2020
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data
This paper delivers improved theoretical guarantees for the convex progr...
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06/10/2019
Inference and Uncertainty Quantification for Noisy Matrix Completion
Noisy matrix completion aims at estimating a low-rank matrix given only ...
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04/10/2019
A Selective Overview of Deep Learning
Deep learning has arguably achieved tremendous success in recent years. ...
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02/20/2019
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization
This paper studies noisy low-rank matrix completion: given partial and c...
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04/12/2018
Trajectory Factory: Tracklet Cleaving and Re-connection by Deep Siamese Bi-GRU for Multiple Object Tracking
Multi-Object Tracking (MOT) is a challenging task in the complex scene s...
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03/21/2018
Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval
This paper considers the problem of solving systems of quadratic equatio...
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02/17/2018
Nonconvex Matrix Factorization from Rank-One Measurements
We consider the problem of recovering low-rank matrices from random rank...
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11/28/2017
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion and Blind Deconvolution
Recent years have seen a flurry of activities in designing provably effi...
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09/20/2017
Inter-Subject Analysis: Inferring Sparse Interactions with Dense Intra-Graphs
We develop a new modeling framework for Inter-Subject Analysis (ISA). Th...
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07/31/2017