b'Qi Lei'

research

∙ 07/20/2023

Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering

Despite the empirical success and practical significance of (relational)...

0 Yijun Dong, et al. ∙

research

∙ 06/21/2023

Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms

In stochastic zeroth-order optimization, a problem of practical relevanc...

0 Qian Yu, et al. ∙

research

∙ 12/07/2022

Reconstructing Training Data from Model Gradient, Provably

Understanding when and how much a model gradient leaks information about...

0 Zihan Wang, et al. ∙

research

∙ 10/25/2022

COEP: Cascade Optimization for Inverse Problems with Entropy-Preserving Hyperparameter Tuning

We propose COEP, an automated and principled framework to solve inverse ...

0 Tianci Liu, et al. ∙

research

∙ 09/28/2022

Efficient Medical Image Assessment via Self-supervised Learning

High-performance deep learning methods typically rely on large annotated...

9 Chun-Yin Huang, et al. ∙

research

∙ 05/11/2022

Reconnecting the Estranged Relationships: Optimizing the Influence Propagation in Evolving Networks

Influence Maximization (IM), which aims to select a set of users from a ...

0 Taotao Cai, et al. ∙

research

∙ 03/29/2022

Nearly Minimax Algorithms for Linear Bandits with Shared Representation

We give novel algorithms for multi-task and lifelong linear bandits with...

0 Jiaqi Yang, et al. ∙

research

∙ 02/24/2022

Sample Efficiency of Data Augmentation Consistency Regularization

Data augmentation is popular in the training of large neural networks; c...

7 Shuo Yang, et al. ∙

research

∙ 01/22/2022

Bi-CLKT: Bi-Graph Contrastive Learning based Knowledge Tracing

The goal of Knowledge Tracing (KT) is to estimate how well students have...

0 XiangYu Song, et al. ∙

research

∙ 10/18/2021

Provable Hierarchy-Based Meta-Reinforcement Learning

Hierarchical reinforcement learning (HRL) has seen widespread interest a...

12 Kurtland Chua, et al. ∙

research

∙ 07/14/2021

Going Beyond Linear RL: Sample Efficient Neural Function Approximation

Deep Reinforcement Learning (RL) powered by neural net approximation of ...

4 Baihe Huang, et al. ∙

research

∙ 07/09/2021

Optimal Gradient-based Algorithms for Non-concave Bandit Optimization

Bandit problems with linear or concave reward have been extensively stud...

10 Baihe Huang, et al. ∙

research

∙ 07/06/2021

A Short Note on the Relationship of Information Gain and Eluder Dimension

Eluder dimension and information gain are two widely used methods of com...

5 Kaixuan Huang, et al. ∙

research

∙ 05/05/2021

How Fine-Tuning Allows for Effective Meta-Learning

Representation learning has been widely studied in the context of meta-l...

4 Kurtland Chua, et al. ∙

research

∙ 02/22/2021

A Theory of Label Propagation for Subpopulation Shift

One of the central problems in machine learning is domain adaptation. Un...

4 Tianle Cai, et al. ∙

research

∙ 10/11/2020

Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev

Sampling is a fundamental and arguably very important task with numerous...

6 Xiao Wang, et al. ∙

research

∙ 08/03/2020

Predicting What You Already Know Helps: Provable Self-Supervised Learning

Self-supervised representation learning solves auxiliary prediction task...

7 Jason D. Lee, et al. ∙

research

∙ 03/23/2020

Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting

We propose signed splitting steepest descent (S3D), which progressively ...

7 Lemeng Wu, et al. ∙

research

∙ 03/18/2020

Compressed Sensing with Invertible Generative Models and Dependent Noise

We study image inverse problems with invertible generative priors, speci...

11 Jay Whang, et al. ∙

research

∙ 02/21/2020

Few-Shot Learning via Learning the Representation, Provably

This paper studies few-shot learning via representation learning, where ...

46 Simon S. Du, et al. ∙

research

∙ 02/17/2020

CAT: Customized Adversarial Training for Improved Robustness

Adversarial training has become one of the most effective methods for im...

4 Minhao Cheng, et al. ∙

research

∙ 02/17/2020

Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes

In a recent series of papers it has been established that variants of Gr...

10 Qi Lei, et al. ∙

research

∙ 10/17/2019

Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls

Large-scale machine learning training suffers from two prior challenges,...

17 Jiacheng Zhuo, et al. ∙

research

∙ 10/15/2019

SGD Learns One-Layer Networks in WGANs

Generative adversarial networks (GANs) are a widely used framework for l...

44 Qi Lei, et al. ∙

research

∙ 06/18/2019

Inverting Deep Generative models, One layer at a time

We study the problem of inverting a deep generative model with ReLU acti...

23 Qi Lei, et al. ∙

research

∙ 06/06/2019

Primal-Dual Block Frank-Wolfe

We propose a variant of the Frank-Wolfe algorithm for solving a class of...

1 Qi Lei, et al. ∙

research

∙ 12/01/2018

Discrete Attacks and Submodular Optimization with Applications to Text Classification

Adversarial examples are carefully constructed modifications to an input...

0 Qi Lei, et al. ∙

research

∙ 09/14/2018

Random Warping Series: A Random Features Method for Time-Series Embedding

Time series data analytics has been a problem of substantial interests f...

8 Lingfei Wu, et al. ∙

research

∙ 03/25/2018

Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization

Vanishing and exploding gradients are two of the main obstacles in train...

0 Jiong Zhang, et al. ∙

research

∙ 02/22/2018

Hessian-based Analysis of Large Batch Training and Robustness to Adversaries

Large batch size training of Neural Networks has been shown to incur acc...

0 Zhewei Yao, et al. ∙

research

∙ 02/12/2017

Similarity Preserving Representation Learning for Time Series Analysis

A considerable amount of machine learning algorithms take instance-featu...

0 Qi Lei, et al. ∙

research

∙ 09/04/2015

Coordinate Descent Methods for Symmetric Nonnegative Matrix Factorization

Given a symmetric nonnegative matrix A, symmetric nonnegative matrix fac...

0 Arnaud Vandaele, et al. ∙

Qi Lei

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