Yuxin Chen

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Princeton University ∙ The University of Chicago ∙ Stanford University ∙ California Institute of Technology ∙ The Ohio State University

Assistant professor in the Department of Electrical Engineering and an associated faculty member in the Department of Computer Science at Princeton University

Softmax Policy Gradient Methods Can Take Exponential Time to Converge

The softmax policy gradient (PG) method, which performs gradient ascent ...
02/22/2021 ∙ by Gen Li, et al. ∙ 6 ∙ share

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Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning

Q-learning, which seeks to learn the optimal Q-function of a Markov deci...
02/12/2021 ∙ by Gen Li, et al. ∙ 4 ∙ share

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Spectral Methods for Data Science: A Statistical Perspective

Spectral methods have emerged as a simple yet surprisingly effective app...
12/15/2020 ∙ by Yuxin Chen, et al. ∙ 18 ∙ share

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Preference-Based Batch and Sequential Teaching

Algorithmic machine teaching studies the interaction between a teacher a...
10/17/2020 ∙ by Farnam Mansouri, et al. ∙ 1 ∙ share

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Learning Time Varying Risk Preferences from Investment Portfolios using Inverse Optimization with Applications on Mutual Funds

The fundamental principle in Modern Portfolio Theory (MPT) is based on t...
10/04/2020 ∙ by Shi Yu, et al. ∙ 0 ∙ share

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Learning Mixtures of Low-Rank Models

We study the problem of learning mixtures of low-rank models, i.e. recon...
09/23/2020 ∙ by Yanxi Chen, et al. ∙ 22 ∙ share

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Using Ensemble Classifiers to Detect Incipient Anomalies

Incipient anomalies present milder symptoms compared to severe ones, and...
08/20/2020 ∙ by Baihong Jin, et al. ∙ 5 ∙ share

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Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution

We investigate the effectiveness of convex relaxation and nonconvex opti...
08/04/2020 ∙ by Yuxin Chen, et al. ∙ 21 ∙ share

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Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization

Natural policy gradient (NPG) methods are among the most widely used pol...
07/13/2020 ∙ by Shicong Cen, et al. ∙ 9 ∙ share

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Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI

Ensemble learning is widely applied in Machine Learning (ML) to improve ...
07/12/2020 ∙ by Yingshui Tan, et al. ∙ 9 ∙ share

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Are Ensemble Classifiers Powerful Enough for the Detection and Diagnosis of Intermediate-Severity Faults?

IS faults present milder symptoms compared to severe faults, and are mor...
07/07/2020 ∙ by Baihong Jin, et al. ∙ 0 ∙ share

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Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries

We examine the task of locating a target region among those induced by i...
06/25/2020 ∙ by Akash Kumar, et al. ∙ 4 ∙ share

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Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality

We study the distribution and uncertainty of nonconvex optimization for ...
06/15/2020 ∙ by Changxiao Cai, et al. ∙ 7 ∙ share

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

Asynchronous Q-learning aims to learn the optimal action-value function ...
06/04/2020 ∙ by Gen Li, et al. ∙ 11 ∙ share

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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...
05/26/2020 ∙ by Gen Li, et al. ∙ 4 ∙ share

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Understanding the Power and Limitations of Teaching with Imperfect Knowledge

Machine teaching studies the interaction between a teacher and a student...
03/21/2020 ∙ by Rati Devidze, et al. ∙ 14 ∙ share

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An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles

Energy-efficient navigation constitutes an important challenge in electr...
03/03/2020 ∙ by Niklas Åkerblom, et al. ∙ 8 ∙ share

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A Financial Service Chatbot based on Deep Bidirectional Transformers

We develop a chatbot using Deep Bidirectional Transformer models (BERT) ...
02/17/2020 ∙ by Shi Yu, et al. ∙ 0 ∙ share

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Adaptive Teaching of Temporal Logic Formulas to Learners with Preferences

Machine teaching is an algorithmic framework for teaching a target hypot...
01/27/2020 ∙ by Zhe Xu, et al. ∙ 0 ∙ share

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Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data

This paper delivers improved theoretical guarantees for the convex progr...
01/15/2020 ∙ by Yuxin Chen, et al. ∙ 19 ∙ share

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Inference for linear forms of eigenvectors under minimal eigenvalue separation: Asymmetry and heteroscedasticity

A fundamental task that spans numerous applications is inference and unc...
01/14/2020 ∙ by Chen Cheng, et al. ∙ 10 ∙ share

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Nonconvex Low-Rank Symmetric Tensor Completion from Noisy Data

We study a noisy symmetric tensor completion problem of broad practical ...
11/11/2019 ∙ by Changxiao Cai, et al. ∙ 0 ∙ share

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Landmark Ordinal Embedding

In this paper, we aim to learn a low-dimensional Euclidean representatio...
10/27/2019 ∙ by Nikhil Ghosh, et al. ∙ 19 ∙ share

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Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models

Algorithmic machine teaching studies the interaction between a teacher a...
10/24/2019 ∙ by Farnam Mansouri, et al. ∙ 0 ∙ share

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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...
10/09/2019 ∙ by Changxiao Cai, et al. ∙ 0 ∙ share

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RDMA vs. RPC for Implementing Distributed Data Structures

Distributed data structures are key to implementing scalable application...
10/04/2019 ∙ by Benjamin Brock, et al. ∙ 0 ∙ share

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Nailed It: Autonomous Roofing with a Nailgun-Equipped Octocopter

This paper presents the first demonstration of autonomous roofing with a...
09/18/2019 ∙ by Matthew Romano, et al. ∙ 0 ∙ share

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Communication-Efficient Distributed Optimization in Networks with Gradient Tracking

There is a growing interest in large-scale machine learning and optimiza...
09/12/2019 ∙ by Boyue Li, et al. ∙ 0 ∙ share

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Augmenting Monte Carlo Dropout Classification Models with Unsupervised Learning Tasks for Detecting and Diagnosing Out-of-Distribution Faults

The Monte Carlo dropout method has proved to be a scalable and easy-to-u...
09/10/2019 ∙ by Baihong Jin, et al. ∙ 19 ∙ share

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An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing

We present a novel unsupervised deep learning approach that utilizes the...
07/26/2019 ∙ by Baihong Jin, et al. ∙ 8 ∙ share

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Inference and Uncertainty Quantification for Noisy Matrix Completion

Noisy matrix completion aims at estimating a low-rank matrix given only ...
06/10/2019 ∙ by Yuxin Chen, et al. ∙ 0 ∙ share

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Understanding the Effectiveness of Ultrasonic Microphone Jammer

Recent works have explained the principle of using ultrasonic transmissi...
04/17/2019 ∙ by Yuxin Chen, et al. ∙ 0 ∙ share

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Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design

In many high-throughput experimental design settings, such as those comm...
04/17/2019 ∙ by Kevin K. Yang, et al. ∙ 10 ∙ share

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AED-Net: An Abnormal Event Detection Network

It is challenging to detect the anomaly in crowded scenes for quite a lo...
03/28/2019 ∙ by Tian Wang, et al. ∙ 14 ∙ share

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Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization

This paper studies noisy low-rank matrix completion: given partial and c...
02/20/2019 ∙ by Yuxin Chen, et al. ∙ 0 ∙ share

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A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection

It is important to identify the change point of a system's health status...
02/18/2019 ∙ by Baihong Jin, et al. ∙ 0 ∙ share

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Trip Prediction by Leveraging Trip Histories from Neighboring Users

We propose a novel approach for trip prediction by analyzing user's trip...
12/25/2018 ∙ by Yuxin Chen, et al. ∙ 0 ∙ share

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Asymmetry Helps: Eigenvalue and Eigenvector Analyses of Asymmetrically Perturbed Low-Rank Matrices

This paper is concerned with a curious phenomenon in spectral estimation...
11/30/2018 ∙ by Yuxin Chen, et al. ∙ 0 ∙ share

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Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes

We apply numerical methods in combination with finite-difference-time-do...
11/15/2018 ∙ by Jialin Song, et al. ∙ 0 ∙ share

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A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes

How can we efficiently gather information to optimize an unknown functio...
11/02/2018 ∙ by Jialin Song, et al. ∙ 12 ∙ share

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Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks

Semantic segmentation is one of the basic topics in computer vision, it ...
11/01/2018 ∙ by Shuangting Liu, et al. ∙ 0 ∙ share

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Adversarial WiFi Sensing using a Single Smartphone

Wireless devices are everywhere, at home, at the office, and on the stre...
10/23/2018 ∙ by Yanzi Zhu, et al. ∙ 0 ∙ share

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Adversarial WiFi Sensing

Wireless devices are everywhere, at home, at the office, and on the stre...
10/23/2018 ∙ by Yanzi Zhu, et al. ∙ 0 ∙ share

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Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview

Substantial progress has been made recently on developing provably accur...
09/25/2018 ∙ by Yuejie Chi, et al. ∙ 0 ∙ share

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Seeding Deep Learning using Wireless Localization

Deep learning is often constrained by the lack of large, diverse labeled...
09/22/2018 ∙ by Zhujun Xiao, et al. ∙ 0 ∙ share

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Teaching Multiple Concepts to Forgetful Learners

How can we help a forgetful learner learn multiple concepts within a lim...
05/21/2018 ∙ by Anette Hunziker, et al. ∙ 0 ∙ share

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Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval

This paper considers the problem of solving systems of quadratic equatio...
03/21/2018 ∙ by Yuxin Chen, et al. ∙ 0 ∙ share

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Teaching Categories to Human Learners with Visual Explanations

We study the problem of computer-assisted teaching with explanations. Co...
02/20/2018 ∙ by Oisin Mac Aodha, et al. ∙ 0 ∙ share

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Nonconvex Matrix Factorization from Rank-One Measurements

We consider the problem of recovering low-rank matrices from random rank...
02/17/2018 ∙ by Yuanxin Li, et al. ∙ 0 ∙ share

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Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners

In real-world applications of education and human teaching, an effective...
02/14/2018 ∙ by Yuxin Chen, et al. ∙ 0 ∙ share

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Yuxin Chen

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