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05/31/2023
Federated Learning in the Presence of Adversarial Client Unavailability
Federated learning is a decentralized machine learning framework wherein...
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09/25/2022
Random graph matching at Otter's threshold via counting chandeliers
We propose an efficient algorithm for graph matching based on similarity...
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06/15/2022
Global Convergence of Federated Learning for Mixed Regression
This paper studies the problem of model training under Federated Learnin...
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05/26/2022
SeedGNN: Graph Neural Networks for Supervised Seeded Graph Matching
Recently, there have been significant interests in designing Graph Neura...
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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...
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11/07/2021
LiMuSE: Lightweight Multi-modal Speaker Extraction
The past several years have witnessed significant progress in modeling t...
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10/22/2021
Testing network correlation efficiently via counting trees
We propose a new procedure for testing whether two networks are edge-cor...
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06/29/2021
Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points
Federated Learning (FL) is a promising framework that has great potentia...
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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...
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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...
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04/17/2021
MIMO Self-attentive RNN Beamformer for Multi-speaker Speech Separation
Recently, our proposed recurrent neural network (RNN) based all deep lea...
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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 ...
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02/23/2021
Learner-Private Online Convex Optimization
Online convex optimization is a framework where a learner sequentially q...
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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...
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02/08/2021
Speaker and Direction Inferred Dual-channel Speech Separation
Most speech separation methods, trying to separate all channel sources s...
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01/29/2021
Settling the Sharp Reconstruction Thresholds of Random Graph Matching
This paper studies the problem of recovering the hidden vertex correspon...
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11/29/2020
Audio-visual Speech Separation with Adversarially Disentangled Visual Representation
Speech separation aims to separate individual voice from an audio mixtur...
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08/23/2020
Testing correlation of unlabeled random graphs
We study the problem of detecting the edge correlation between two rando...
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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...
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06/25/2020
Speaker-Conditional Chain Model for Speech Separation and Extraction
Speech separation has been extensively explored to tackle the cocktail p...
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04/08/2020
Graph Matching with Partially-Correct Seeds
The graph matching problem aims to find the latent vertex correspondence...
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12/30/2019
All-or-Nothing Phenomena: From Single-Letter to High Dimensions
We consider the linear regression problem of estimating a p-dimensional ...
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12/18/2019
The Planted Matching Problem: Phase Transitions and Exact Results
We study the problem of recovering a planted matching in randomly weight...
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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...
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11/18/2019
Consistent recovery threshold of hidden nearest neighbor graphs
Motivated by applications such as discovering strong ties in social netw...
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09/21/2019
Optimal query complexity for private sequential learning
Motivated by privacy concerns in many practical applications such as Fed...
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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...
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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...
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05/06/2019
POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion
Increasing demand for fashion recommendation raises a lot of challenges ...
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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...
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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×...
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11/19/2018
Efficient random graph matching via degree profiles
Random graph matching refers to recovering the underlying vertex corresp...
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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 ...
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09/30/2018
Convex Relaxation Methods for Community Detection
This paper surveys recent theoretical advances in convex optimization ap...
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09/06/2018
Cascaded Mutual Modulation for Visual Reasoning
Visual reasoning is a special visual question answering problem that is ...
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07/26/2018
Seeded Graph Matching via Large Neighborhood Statistics
We study a well known noisy model of the graph isomorphism problem. In t...
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05/31/2018
Statistical Problems with Planted Structures: Information-Theoretical and Computational Limits
Over the past few years, insights from computer science, statistical phy...
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04/26/2018
Securing Distributed Machine Learning in High Dimensions
We consider securing a distributed machine learning system wherein the d...
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04/15/2018
Hidden Hamiltonian Cycle Recovery via Linear Programming
We introduce the problem of hidden Hamiltonian cycle recovery, where the...
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09/10/2017
Rates of Convergence of Spectral Methods for Graphon Estimation
This paper studies the problem of estimating the grahpon model - the und...
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05/16/2017
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
We consider the problem of distributed statistical machine learning in a...
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04/24/2017
Learning from Comparisons and Choices
When tracking user-specific online activities, each user's preference is...
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01/01/2017
Self-Taught Convolutional Neural Networks for Short Text Clustering
Short text clustering is a challenging problem due to its sparseness of ...
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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 ...
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09/28/2016
Hierarchical Memory Networks for Answer Selection on Unknown Words
Recently, end-to-end memory networks have shown promising results on Que...
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02/20/2016
Semidefinite Programs for Exact Recovery of a Hidden Community
We study a semidefinite programming (SDP) relaxation of the maximum like...
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12/28/2015
Convexified Modularity Maximization for Degree-corrected Stochastic Block Models
The stochastic block model (SBM) is a popular framework for studying com...
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10/30/2015
Submatrix localization via message passing
The principal submatrix localization problem deals with recovering a K× ...
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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 ...
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09/25/2015
