b'Jiaming Xu'

research

∙ 05/31/2023

Federated Learning in the Presence of Adversarial Client Unavailability

Federated learning is a decentralized machine learning framework wherein...

0 Lili Su, et al. ∙

research

∙ 09/25/2022

Random graph matching at Otter's threshold via counting chandeliers

We propose an efficient algorithm for graph matching based on similarity...

0 Cheng Mao, et al. ∙

research

∙ 06/15/2022

Global Convergence of Federated Learning for Mixed Regression

This paper studies the problem of model training under Federated Learnin...

0 Lili Su, et al. ∙

research

∙ 05/26/2022

SeedGNN: Graph Neural Networks for Supervised Seeded Graph Matching

Recently, there have been significant interests in designing Graph Neura...

0 Liren Yu, et al. ∙

research

∙ 02/22/2022

Random Graph Matching in Geometric Models: the Case of Complete Graphs

This paper studies the problem of matching two complete graphs with edge...

0 Haoyu Wang, et al. ∙

research

∙ 11/07/2021

LiMuSE: Lightweight Multi-modal Speaker Extraction

The past several years have witnessed significant progress in modeling t...

0 Qinghua Liu, et al. ∙

research

∙ 10/22/2021

Testing network correlation efficiently via counting trees

We propose a new procedure for testing whether two networks are edge-cor...

0 Cheng Mao, et al. ∙

research

∙ 06/29/2021

Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points

Federated Learning (FL) is a promising framework that has great potentia...

0 Lili Su, et al. ∙

research

∙ 06/13/2021

WASE: Learning When to Attend for Speaker Extraction in Cocktail Party Environments

In the speaker extraction problem, it is found that additional informati...

0 Yunzhe Hao, et al. ∙

research

∙ 05/01/2021

One-pass Stochastic Gradient Descent in Overparametrized Two-layer Neural Networks

There has been a recent surge of interest in understanding the convergen...

0 Jiaming Xu, et al. ∙

research

∙ 04/17/2021

MIMO Self-attentive RNN Beamformer for Multi-speaker Speech Separation

Recently, our proposed recurrent neural network (RNN) based all deep lea...

0 Xiyun Li, et al. ∙

research

∙ 03/17/2021

The planted matching problem: Sharp threshold and infinite-order phase transition

We study the problem of reconstructing a perfect matching M^* hidden in ...

0 Jian Ding, et al. ∙

research

∙ 02/23/2021

Learner-Private Online Convex Optimization

Online convex optimization is a framework where a learner sequentially q...

0 Jiaming Xu, et al. ∙

research

∙ 02/23/2021

The Power of D-hops in Matching Power-Law Graphs

This paper studies seeded graph matching for power-law graphs. Assume th...

0 Liren Yu, et al. ∙

research

∙ 02/08/2021

Speaker and Direction Inferred Dual-channel Speech Separation

Most speech separation methods, trying to separate all channel sources s...

0 Chenxing Li, et al. ∙

research

∙ 01/29/2021

Settling the Sharp Reconstruction Thresholds of Random Graph Matching

This paper studies the problem of recovering the hidden vertex correspon...

0 Yihong Wu, et al. ∙

research

∙ 11/29/2020

Audio-visual Speech Separation with Adversarially Disentangled Visual Representation

Speech separation aims to separate individual voice from an audio mixtur...

0 Peng Zhang, et al. ∙

research

∙ 08/23/2020

Testing correlation of unlabeled random graphs

We study the problem of detecting the edge correlation between two rando...

0 Yihong Wu, et al. ∙

research

∙ 06/25/2020

Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture Signals

Neural sequence-to-sequence models are well established for applications...

0 Jing Shi, et al. ∙

research

∙ 06/25/2020

Speaker-Conditional Chain Model for Speech Separation and Extraction

Speech separation has been extensively explored to tackle the cocktail p...

0 Jing Shi, et al. ∙

research

∙ 04/08/2020

Graph Matching with Partially-Correct Seeds

The graph matching problem aims to find the latent vertex correspondence...

0 Liren Yu, et al. ∙

research

∙ 12/30/2019

All-or-Nothing Phenomena: From Single-Letter to High Dimensions

We consider the linear regression problem of estimating a p-dimensional ...

0 Galen Reeves, et al. ∙

research

∙ 12/18/2019

The Planted Matching Problem: Phase Transitions and Exact Results

We study the problem of recovering a planted matching in randomly weight...

22 Mehrdad Moharrami, et al. ∙

research

∙ 12/18/2019

DMRM: A Dual-channel Multi-hop Reasoning Model for Visual Dialog

Visual Dialog is a vision-language task that requires an AI agent to eng...

0 Feilong Chen, et al. ∙

research

∙ 11/18/2019

Consistent recovery threshold of hidden nearest neighbor graphs

Motivated by applications such as discovering strong ties in social netw...

0 Jian Ding, et al. ∙

research

∙ 09/21/2019

Optimal query complexity for private sequential learning

Motivated by privacy concerns in many practical applications such as Fed...

0 Jiaming Xu, et al. ∙

research

∙ 07/20/2019

Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality

We analyze a new spectral graph matching algorithm, GRAph Matching by Pa...

0 Zhou Fan, et al. ∙

research

∙ 07/20/2019

Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model

Graph matching aims at finding the vertex correspondence between two unl...

0 Zhou Fan, et al. ∙

research

∙ 05/06/2019

POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion

Increasing demand for fashion recommendation raises a lot of challenges ...

0 Wen Chen, et al. ∙

research

∙ 03/12/2019

The All-or-Nothing Phenomenon in Sparse Linear Regression

We study the problem of recovering a hidden binary k-sparse p-dimensiona...

0 Galen Reeves, et al. ∙

research

∙ 03/01/2019

Improved queue-size scaling for input-queued switches via graph factorization

This paper studies the scaling of the expected total queue size in an n×...

0 Jiaming Xu, et al. ∙

research

∙ 11/19/2018

Efficient random graph matching via degree profiles

Random graph matching refers to recovering the underlying vertex corresp...

0 Jian Ding, et al. ∙

research

∙ 11/15/2018

Concept Learning through Deep Reinforcement Learning with Memory-Augmented Neural Networks

Deep neural networks have shown superior performance in many regimes to ...

8 Jing Shi, et al. ∙

research

∙ 09/30/2018

Convex Relaxation Methods for Community Detection

This paper surveys recent theoretical advances in convex optimization ap...

0 Xiaodong Li, et al. ∙

research

∙ 09/06/2018

Cascaded Mutual Modulation for Visual Reasoning

Visual reasoning is a special visual question answering problem that is ...

0 Yiqun Yao, et al. ∙

research

∙ 07/26/2018

Seeded Graph Matching via Large Neighborhood Statistics

We study a well known noisy model of the graph isomorphism problem. In t...

0 Elchanan Mossel, et al. ∙

research

∙ 05/31/2018

Statistical Problems with Planted Structures: Information-Theoretical and Computational Limits

Over the past few years, insights from computer science, statistical phy...

0 Yihong Wu, et al. ∙

research

∙ 04/26/2018

Securing Distributed Machine Learning in High Dimensions

We consider securing a distributed machine learning system wherein the d...

0 Lili Su, et al. ∙

research

∙ 04/15/2018

Hidden Hamiltonian Cycle Recovery via Linear Programming

We introduce the problem of hidden Hamiltonian cycle recovery, where the...

0 Vivek Bagaria, et al. ∙

research

∙ 09/10/2017

Rates of Convergence of Spectral Methods for Graphon Estimation

This paper studies the problem of estimating the grahpon model - the und...

0 Jiaming Xu, et al. ∙

research

∙ 05/16/2017

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent

We consider the problem of distributed statistical machine learning in a...

0 Yudong Chen, et al. ∙

research

∙ 04/24/2017

Learning from Comparisons and Choices

When tracking user-specific online activities, each user's preference is...

0 Sahand Negahban, et al. ∙

research

∙ 01/01/2017

Self-Taught Convolutional Neural Networks for Short Text Clustering

Short text clustering is a challenging problem due to its sparseness of ...

0 Jiaming Xu, et al. ∙

research

∙ 11/21/2016

Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling

Recurrent Neural Network (RNN) is one of the most popular architectures ...

0 Peng Zhou, et al. ∙

research

∙ 09/28/2016

Hierarchical Memory Networks for Answer Selection on Unknown Words

Recently, end-to-end memory networks have shown promising results on Que...

0 Jiaming Xu, et al. ∙

research

∙ 02/20/2016

Semidefinite Programs for Exact Recovery of a Hidden Community

We study a semidefinite programming (SDP) relaxation of the maximum like...

0 Bruce Hajek, et al. ∙

research

∙ 12/28/2015

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models

The stochastic block model (SBM) is a popular framework for studying com...

0 Yudong Chen, et al. ∙

research

∙ 10/30/2015

Submatrix localization via message passing

The principal submatrix localization problem deals with recovering a K× ...

0 Bruce Hajek, et al. ∙

research

∙ 10/09/2015

Recovering a Hidden Community Beyond the Spectral Limit in O(|E| ^*|V|) Time

Community detection is considered for a stochastic block model graph of ...

0 Bruce Hajek, et al. ∙

research

∙ 09/25/2015

Information Limits for Recovering a Hidden Community

We study the problem of recovering a hidden community of cardinality K f...

0 Bruce Hajek, et al. ∙

Jiaming Xu

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