b'Yuan Zhou'

research

∙ 05/26/2023

ABC-KD: Attention-Based-Compression Knowledge Distillation for Deep Learning-Based Noise Suppression

Noise suppression (NS) models have been widely applied to enhance speech...

0 Yixin Wan, et al. ∙

research

∙ 05/18/2023

Advancing Incremental Few-shot Semantic Segmentation via Semantic-guided Relation Alignment and Adaptation

Incremental few-shot semantic segmentation (IFSS) aims to incrementally ...

0 Yuan Zhou, et al. ∙

research

∙ 04/21/2023

Solid angle measure of polyhedral cones

This paper addresses the computation of normalized solid angle measure o...

0 Allison Fitisone, et al. ∙

research

∙ 04/20/2023

High-Fidelity and Freely Controllable Talking Head Video Generation

Talking head generation is to generate video based on a given source ide...

0 Yue Gao, et al. ∙

research

∙ 03/08/2023

RAF: Holistic Compilation for Deep Learning Model Training

As deep learning is pervasive in modern applications, many deep learning...

0 Cody Hao Yu, et al. ∙

research

∙ 02/25/2023

Medical visual question answering using joint self-supervised learning

Visual Question Answering (VQA) becomes one of the most active research ...

0 Yuan Zhou, et al. ∙

research

∙ 10/15/2022

Near-Optimal Regret Bounds for Multi-batch Reinforcement Learning

In this paper, we study the episodic reinforcement learning (RL) probl...

0 Zihan Zhang, et al. ∙

research

∙ 09/30/2022

Assortment Optimization Under the Multivariate MNL Model

We study an assortment optimization problem under a multi-purchase choic...

0 Xin Chen, et al. ∙

research

∙ 09/27/2022

Bayesian-Nash-Incentive-Compatible Mechanism for Blockchain Transaction Fee Allocation

In blockchain systems, the design of transaction fee mechanisms is essen...

0 Zishuo Zhao, et al. ∙

research

∙ 08/03/2022

AACC: Asymmetric Actor-Critic in Contextual Reinforcement Learning

Reinforcement Learning (RL) techniques have drawn great attention in man...

2 Wangyang Yue, et al. ∙

research

∙ 07/22/2022

Fairness-aware Network Revenue Management with Demand Learning

In addition to maximizing the total revenue, decision-makers in lots of ...

2 Xi Chen, et al. ∙

research

∙ 07/13/2022

Dynamic Car Dispatching and Pricing: Revenue and Fairness for Ridesharing Platforms

A major challenge for ridesharing platforms is to guarantee profit and f...

0 Zishuo Zhao, et al. ∙

research

∙ 05/04/2022

Dual Branch Neural Network for Sea Fog Detection in Geostationary Ocean Color Imager

Sea fog significantly threatens the safety of maritime activities. This ...

1 Yuan Zhou, et al. ∙

research

∙ 04/25/2022

Imitation Learning from Observations under Transition Model Disparity

Learning to perform tasks by leveraging a dataset of expert observations...

1 Tanmay Gangwani, et al. ∙

research

∙ 03/02/2022

Clean-Annotation Backdoor Attack against Lane Detection Systems in the Wild

We present the first backdoor attack against the lane detection systems ...

3 Xingshuo Han, et al. ∙

research

∙ 12/27/2021

Self-normalized Classification of Parkinson's Disease DaTscan Images

Classifying SPECT images requires a preprocessing step which normalizes ...

12 Yuan Zhou, et al. ∙

research

∙ 11/26/2021

Learning Long-Term Reward Redistribution via Randomized Return Decomposition

Many practical applications of reinforcement learning require agents to ...

6 Zhizhou Ren, et al. ∙

research

∙ 11/16/2021

Fairness-aware Online Price Discrimination with Nonparametric Demand Models

Price discrimination, which refers to the strategy of setting different ...

4 Xi Chen, et al. ∙

research

∙ 11/13/2021

Full-attention based Neural Architecture Search using Context Auto-regression

Self-attention architectures have emerged as a recent advancement for im...

19 Yuan Zhou, et al. ∙

research

∙ 10/15/2021

Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits

We study the optimal batch-regret tradeoff for batch linear contextual b...

5 Zihan Zhang, et al. ∙

research

∙ 08/13/2021

SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation

Automated segmentation in medical image analysis is a challenging task t...

10 Chenyu You, et al. ∙

research

∙ 07/12/2021

Few-shot Learning with Global Relatedness Decoupled-Distillation

Despite the success that metric learning based approaches have achieved ...

1 Yuan Zhou, et al. ∙

research

∙ 07/11/2021

Coordinate-wise Control Variates for Deep Policy Gradients

The control variates (CV) method is widely used in policy gradient estim...

3 Yuanyi Zhong, et al. ∙

research

∙ 06/22/2021

Off-Policy Reinforcement Learning with Delayed Rewards

We study deep reinforcement learning (RL) algorithms with delayed reward...

4 Beining Han, et al. ∙

research

∙ 05/05/2021

MCGNet: Partial Multi-view Few-shot Learning via Meta-alignment and Context Gated-aggregation

In this paper, we propose a new challenging task named as partial multi-...

6 Yuan Zhou, et al. ∙

research

∙ 01/13/2021

Adversarial Sample Enhanced Domain Adaptation: A Case Study on Predictive Modeling with Electronic Health Records

With the successful adoption of machine learning on electronic health re...

8 Yiqin Yu, et al. ∙

research

∙ 11/05/2020

Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity

Quality-Diversity (QD) is a concept from Neuroevolution with some intrig...

2 Tanmay Gangwani, et al. ∙

research

∙ 10/23/2020

Learning Guidance Rewards with Trajectory-space Smoothing

Long-term temporal credit assignment is an important challenge in deep r...

7 Tanmay Gangwani, et al. ∙

research

∙ 10/15/2020

Unsupervised Self-training Algorithm Based on Deep Learning for Optical Aerial Images Change Detection

Optical aerial images change detection is an important task in earth obs...

9 Yuan Zhou, et al. ∙

research

∙ 10/10/2020

SYMPAIS: SYMbolic Parallel Adaptive Importance Sampling for Probabilistic Program Analysis

Probabilistic software analysis aims at quantifying the probability of a...

5 Yicheng Luo, et al. ∙

research

∙ 10/01/2020

Bayesian Policy Search for Stochastic Domains

AI planning can be cast as inference in probabilistic models, and probab...

0 David Tolpin, et al. ∙

research

∙ 10/01/2020

Probabilistic Programs with Stochastic Conditioning

We tackle the problem of conditioning probabilistic programs on distribu...

0 David Tolpin, et al. ∙

research

∙ 09/26/2020

Near-Optimal MNL Bandits Under Risk Criteria

We study MNL bandits, which is a variant of the traditional multi-armed ...

0 Guangyu Xi, et al. ∙

research

∙ 09/13/2020

Efficient Competitive Self-Play Policy Optimization

Reinforcement learning from self-play has recently reported many success...

11 Yuanyi Zhong, et al. ∙

research

∙ 08/19/2020

Generating Adjacency Matrix for Video-Query based Video Moment Retrieval

In this paper, we continue our work on Video-Query based Video Moment re...

0 Yuan Zhou, et al. ∙

research

∙ 07/29/2020

Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis

Understanding how certain brain regions relate to a specific neurologica...

26 Xiaoxiao Li, et al. ∙

research

∙ 07/20/2020

Graph Neural Network for Video-Query based Video Moment Retrieval

In this paper, we focus on Video Query based Video Moment Retrieval (VQ-...

0 Yuan Zhou, et al. ∙

research

∙ 07/09/2020

Multinomial Logit Bandit with Low Switching Cost

We study multinomial logit bandit with limited adaptivity, where the alg...

4 Kefan Dong, et al. ∙

research

∙ 07/04/2020

Linear Bandits with Limited Adaptivity and Learning Distributional Optimal Design

Motivated by practical needs such as large-scale learning, we study the ...

0 Yufei Ruan, et al. ∙

research

∙ 06/06/2020

Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity

In this paper we consider the problem of learning an ϵ-optimal policy fo...

0 Zihan Zhang, et al. ∙

research

∙ 05/22/2020

Bi-direction Context Propagation Network for Real-time Semantic Segmentation

Spatial details and context correlations are two types of critical infor...

0 Shijie Hao, et al. ∙

research

∙ 05/13/2020

Adaptive Double-Exploration Tradeoff for Outlier Detection

We study a variant of the thresholding bandit problem (TBP) in the conte...

0 Xiaojin Zhang, et al. ∙

research

∙ 04/27/2020

Multi-IF : An Approach to Anomaly Detection in Self-Driving Systems

Autonomous driving vehicles (ADVs) are implemented with rich software fu...

0 Kun Cheng, et al. ∙

research

∙ 04/21/2020

Almost Optimal Model-Free Reinforcement Learning via Reference-Advantage Decomposition

We study the reinforcement learning problem in the setting of finite-hor...

0 Zihan Zhang, et al. ∙

research

∙ 04/20/2020

Collaborative Top Distribution Identifications with Limited Interaction

We consider the following problem in this paper: given a set of n distri...

0 Nikolai Karpov, et al. ∙

research

∙ 03/22/2020

Guardauto: A Decentralized Runtime Protection System for Autonomous Driving

Due to the broad attack surface and the lack of runtime protection, pote...

0 Kun Cheng, et al. ∙

research

∙ 03/02/2020

Stochastically Differentiable Probabilistic Programs

Probabilistic programs with mixed support (both continuous and discrete ...

0 David Tolpin, et al. ∙

research

∙ 03/01/2020

Soft-Root-Sign Activation Function

The choice of activation function in deep networks has a significant eff...

0 Yuan Zhou, et al. ∙

research

∙ 02/22/2020

Anypath Routing Protocol Design via Q-Learning for Underwater Sensor Networks

As a promising technology in the Internet of Underwater Things, underwat...

0 Yuan Zhou, et al. ∙

research

∙ 02/20/2020

Domain Adaptive Adversarial Learning Based on Physics Model Feedback for Underwater Image Enhancement

Owing to refraction, absorption, and scattering of light by suspended pa...

0 Yuan Zhou, et al. ∙

Yuan Zhou

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