b'Yi Zhou'

research

∙ 05/01/2022

DDDM: a Brain-Inspired Framework for Robust Classification

Despite their outstanding performance in a broad spectrum of real-world ...

Xiyuan Chen, et al. ∙

research

∙ 04/30/2022

SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities

As deep learning advances, there is an ever-growing demand for models ca...

Pengbo Hu, et al. ∙

research

∙ 03/31/2022

Data Sampling Affects the Complexity of Online SGD over Dependent Data

Conventional machine learning applications typically assume that data sa...

Shaocong Ma, et al. ∙

research

∙ 03/21/2022

Delving into the Estimation Shift of Batch Normalization in a Network

Batch normalization (BN) is a milestone technique in deep learning. It n...

Lei Huang, et al. ∙

research

∙ 03/14/2022

Sense Embeddings are also Biased–Evaluating Social Biases in Static and Contextualised Sense Embeddings

Sense embedding learning methods learn different embeddings for the diff...

Yi Zhou, et al. ∙

research

∙ 02/24/2022

A Partition-and-Merge Algorithm for Solving the Steiner Tree Problem in Large Graphs

The Steiner tree problem, which asks for a minimum weighted tree spannin...

Xinyu Wu, et al. ∙

research

∙ 02/17/2022

Desingularization and p-Curvature of Recurrence Operators

Linear recurrence operators in characteristic p are classified by their ...

Yi Zhou, et al. ∙

research

∙ 02/17/2022

Listing Maximal k-Plexes in Large Real-World Graphs

Listing dense subgraphs in large graphs plays a key task in varieties of...

Zhengren Wang, et al. ∙

research

∙ 02/16/2022

Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm Analysis

We address the relatively unexplored problem of hyper-parameter optimiza...

Yi Zhou, et al. ∙

research

∙ 02/08/2022

On the Convergence of Gradient Extrapolation Methods for Unbalanced Optimal Transport

We study the Unbalanced Optimal Transport (UOT) between two measures of ...

Quang Minh Nguyen, et al. ∙

research

∙ 12/22/2021

Accelerated Proximal Alternating Gradient-Descent-Ascent for Nonconvex Minimax Machine Learning

Alternating gradient-descent-ascent (AltGDA) is an optimization algorith...

Ziyi Chen, et al. ∙

research

∙ 12/16/2021

Slot-VPS: Object-centric Representation Learning for Video Panoptic Segmentation

Video Panoptic Segmentation (VPS) aims at assigning a class label to eac...

Yi Zhou, et al. ∙

research

∙ 12/15/2021

FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning

We address the relatively unexplored problem of hyper-parameter optimiza...

Yi Zhou, et al. ∙

research

∙ 11/21/2021

Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks

Despite its great success, deep learning severely suffers from robustnes...

Kaiyuan Liu, et al. ∙

research

∙ 11/05/2021

Event-based Motion Segmentation by Cascaded Two-Level Multi-Model Fitting

Among prerequisites for a synthetic agent to interact with dynamic scene...

Xiuyuan Lu, et al. ∙

research

∙ 10/14/2021

Escaping Saddle Points in Nonconvex Minimax Optimization via Cubic-Regularized Gradient Descent-Ascent

The gradient descent-ascent (GDA) algorithm has been widely applied to s...

Ziyi Chen, et al. ∙

research

∙ 10/05/2021

Learning Sense-Specific Static Embeddings using Contextualised Word Embeddings as a Proxy

Contextualised word embeddings generated from Neural Language Models (NL...

Yi Zhou, et al. ∙

research

∙ 09/23/2021

The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21

This paper describes the Volctrans' submission to the WMT21 news transla...

Lihua Qian, et al. ∙

research

∙ 09/20/2021

Assisted Learning for Organizations with Limited Data

We develop an assisted learning framework for assisting organization-lev...

Cheng Chen, et al. ∙

research

∙ 09/08/2021

Sample and Communication-Efficient Decentralized Actor-Critic Algorithms with Finite-Time Analysis

Actor-critic (AC) algorithms have been widely adopted in decentralized m...

Ziyi Chen, et al. ∙

research

∙ 08/18/2021

Stochastic Scene-Aware Motion Prediction

A long-standing goal in computer vision is to capture, model, and realis...

Mohamed Hassan, et al. ∙

research

∙ 08/18/2021

Specificity-preserving RGB-D Saliency Detection

RGB-D saliency detection has attracted increasing attention, due to its ...

Tao Zhou, et al. ∙

research

∙ 07/26/2021

LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning

Federated learning has arisen as a mechanism to allow multiple participa...

Kamala Varma, et al. ∙

research

∙ 06/17/2021

using multiple losses for accurate facial age estimation

Age estimation is an essential challenge in computer vision. With the ad...

Yi Zhou, et al. ∙

research

∙ 06/16/2021

Improving Entity Linking through Semantic Reinforced Entity Embeddings

Entity embeddings, which represent different aspects of each entity with...

Feng Hou, et al. ∙

research

∙ 06/08/2021

A likelihood based sensitivity analysis for publication bias on summary ROC in meta-analysis of diagnostic test accuracy

In meta-analysis of diagnostic test accuracy, summary receiver operating...

Yi Zhou, et al. ∙

research

∙ 04/07/2021

Finite-Sample Analysis for Two Time-scale Non-linear TDC with General Smooth Function Approximation

Temporal-difference learning with gradient correction (TDC) is a two tim...

Yue Wang, et al. ∙

research

∙ 03/30/2021

Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity

Greedy-GQ is a value-based reinforcement learning (RL) algorithm for opt...

Shaocong Ma, et al. ∙

research

∙ 03/24/2021

Multi-Agent Off-Policy TD Learning: Finite-Time Analysis with Near-Optimal Sample Complexity and Communication Complexity

The finite-time convergence of off-policy TD learning has been comprehen...

Ziyi Chen, et al. ∙

research

∙ 03/05/2021

FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data

Federated learning (FL) has been proposed to allow collaborative trainin...

Runhua Xu, et al. ∙

research

∙ 03/01/2021

A Deep Emulator for Secondary Motion of 3D Characters

Fast and light-weight methods for animating 3D characters are desirable ...

Mianlun Zheng, et al. ∙

research

∙ 02/26/2021

Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification

Chest X-rays are an important and accessible clinical imaging tool for t...

Yi Zhou, et al. ∙

research

∙ 02/09/2021

Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry

The gradient descent-ascent (GDA) algorithm has been widely applied to s...

Ziyi Chen, et al. ∙

research

∙ 02/01/2021

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

Data heterogeneity has been identified as one of the key features in fed...

Syed Zawad, et al. ∙

research

∙ 12/17/2020

Enhancing Balanced Graph Edge Partition with Effective Local Search

Graph partition is a key component to achieve workload balance and reduc...

Zhenyu Guo, et al. ∙

research

∙ 12/16/2020

Event-based Motion Segmentation with Spatio-Temporal Graph Cuts

Identifying independently moving objects is an essential task for dynami...

Yi Zhou, et al. ∙

research

∙ 12/15/2020

Canny-VO: Visual Odometry with RGB-D Cameras based on Geometric 3D-2D Edge Alignment

The present paper reviews the classical problem of free-form curve regis...

Yi Zhou, et al. ∙

research

∙ 12/11/2020

Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning

Federated Learning (FL) is an approach to collaboratively train a model ...

Yuya Jeremy Ong, et al. ∙

research

∙ 12/09/2020

Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation

Acquiring sufficient ground-truth supervision to train deep visual model...

Xueyi Li, et al. ∙

research

∙ 12/04/2020

Mitigating Bias in Federated Learning

As methods to create discrimination-aware models develop, they focus on ...

Annie Abay, et al. ∙

research

∙ 11/25/2020

Multimodal Learning for Hateful Memes Detection

Memes are multimedia documents containing images and phrases that usuall...

Yi Zhou, et al. ∙

research

∙ 11/17/2020

Contrastive Weight Regularization for Large Minibatch SGD

The minibatch stochastic gradient descent method (SGD) is widely applied...

Qiwei Yuan, et al. ∙

research

∙ 11/17/2020

Generating universal language adversarial examples by understanding and enhancing the transferability across neural models

Deep neural network models are vulnerable to adversarial attacks. In man...

Liping Yuan, et al. ∙

research

∙ 11/13/2020

Neural Network Training Techniques Regularize Optimization Trajectory: An Empirical Study

Modern deep neural network (DNN) trainings utilize various training tech...

Cheng Chen, et al. ∙

research

∙ 10/26/2020

Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis

Variance reduction techniques have been successfully applied to temporal...

Shaocong Ma, et al. ∙

research

∙ 10/14/2020

Boosting One-Point Derivative-Free Online Optimization via Residual Feedback

Zeroth-order optimization (ZO) typically relies on two-point feedback to...

Yan Zhang, et al. ∙

research

∙ 10/03/2020

Unsupervised Cross-lingual Image Captioning

Most recent image captioning works are conducted in English as the major...

Jiahui Gao, et al. ∙

research

∙ 09/30/2020

Transfer Learning from Speech Synthesis to Voice Conversion with Non-Parallel Training Data

This paper presents a novel framework to build a voice conversion (VC) s...

Mingyang Zhang, et al. ∙

research

∙ 09/27/2020

Normalization Techniques in Training DNNs: Methodology, Analysis and Application

Normalization techniques are essential for accelerating the training and...

Lei Huang, et al. ∙

research

∙ 09/12/2020

Exploring the Hierarchy in Relation Labels for Scene Graph Generation

By assigning each relationship a single label, current approaches formul...

Yi Zhou, et al. ∙

Yi Zhou

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