604 citations · 2k across the 82 of their papers we have counts for
18 papers · 1 filter
ExtremeBERT: A Toolkit for Accelerating Pretraining of Customized BERT
Rui Pan, Shizhe Diao, Jianlin Chen +1
In this paper, we present ExtremeBERT, a toolkit for accelerating and customizing BERT pretraining. Our goal is to provide an easy-to-use BERT pretraining toolkit for the research…
Normalizing Flow with Variational Latent Representation
Hanze Dong, Shizhe Diao, Weizhong Zhang +1
Normalizing flow (NF) has gained popularity over traditional maximum likelihood based methods due to its strong capability to model complex data distributions. However, the standar…
FAF: A novel multimodal emotion recognition approach integrating face, body and text
Zhongyu Fang, Aoyun He, Qihui Yu +4
Multimodal emotion analysis performed better in emotion recognition depending on more comprehensive emotional clues and multimodal emotion dataset. In this paper, we developed a la…
Prior-mean-assisted Bayesian optimization application on FRIB Front-End tunning
Kilean Hwang, Tomofumi Maruta, Alexander Plastun +5
Bayesian optimization~(BO) is often used for accelerator tuning due to its high sample efficiency. However, the computational scalability of training over large data-set can be pro…
On DoF of Active RIS-Assisted MIMO Interference Channel with Arbitrary Antenna Configurations: When Will RIS Help?
Shuo Zheng, Bojie Lv, Tong Zhang +4
An active reconfigurable intelligent surface (RIS) has been shown to be able to enhance the sum-of-degrees-of-freedom (DoF) of a two-user multiple-input multiple-output (MIMO) inte…
GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond
Han Zhong, Wei Xiong, Sirui Zheng +4
We study sample efficient reinforcement learning (RL) under the general framework of interactive decision making, which includes Markov decision process (MDP), partially observable…
MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation
Ying Su, Zihao Wang, Tianqing Fang +3
Commonsense reasoning tasks such as commonsense knowledge graph completion and commonsense question answering require powerful representation learning. In this paper, we propose to…
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games
Wei Xiong, Han Zhong, Chengshuai Shi +2
Existing studies on provably efficient algorithms for Markov games (MGs) almost exclusively build on the "optimism in the face of uncertainty" (OFU) principle. This work focuses on…
Optimality of the Proper Gaussian Signal in Complex MIMO Wiretap Channels
Yong Dong, Yinfei Xu, Tong Zhang +1
The multiple-input multiple-output (MIMO) wiretap channel (WTC), which has a transmitter, a legitimate user and an eavesdropper, is a classic model for studying information theoret…
Optimal Operation of a Tidal Lagoon as a Flexible Source of Electricity
Tong Zhang, Christopher Williams, Reza Ahmadian +1
As the demand for electricity and the need for power systems flexibility grow, it is crucial to exploit more reliable and clean sources of energy to produce electricity when needed…
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning
Christoph Dann, Mehryar Mohri, Tong Zhang +1
Thompson Sampling is one of the most effective methods for contextual bandits and has been generalized to posterior sampling for certain MDP settings. However, existing posterior s…
Two-person Graph Convolutional Network for Skeleton-based Human Interaction Recognition
Zhengcen Li, Yueran Li, Linlin Tang +2
Graph convolutional networks (GCNs) have been the predominant methods in skeleton-based human action recognition, including human-human interaction recognition. However, when deali…
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity
Alekh Agarwal, Tong Zhang
We propose a general framework to design posterior sampling methods for model-based RL. We show that the proposed algorithms can be analyzed by reducing regret to Hellinger distanc…
The Generalized Degrees-of-Freedom of the Asymmetric Interference Channel with Delayed CSIT
Tong Zhang, Yufan Zhuang, Yinfei Xu
In this paper, we investigate the generalized degrees-of-freedom (GDoF) of the asymmetric interference channel with delayed channel state information at the transmitter (CSIT), whe…
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
Wei Xiong, Han Zhong, Chengshuai Shi +3
Offline reinforcement learning (RL) aims at learning an optimal strategy using a pre-collected dataset without further interactions with the environment. While various algorithms h…
The DoF Region of Two-User MIMO Broadcast Channel with Delayed Imperfect-Quality CSIT
Tong Zhang
The channel state information at the transmitter (CSIT) play an important role in the performance of wireless networks. The CSIT model can be delayed and imperfect-quality, since t…
Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling
Alekh Agarwal, Tong Zhang
Provably sample-efficient Reinforcement Learning (RL) with rich observations and function approximation has witnessed tremendous recent progress, particularly when the underlying f…
Secure Rate-Splitting for MIMO Broadcast Channel with Imperfect CSIT and a Jammer
Tong Zhang, Dongsheng Chen, Na Li +3
In this paper, we investigate the secure rate-splitting for the two-user multiple-input multiple-output (MIMO) broadcast channel with imperfect channel state information at the tra…