422 citations · 673 across the 48 of their papers we have counts for
48 papers
Carbon-Aware Optimal Power Flow
Xin Chen, Andy Sun, Wenbo Shi +1
To facilitate effective decarbonization of the electric power sector, this paper introduces the generic Carbon-aware Optimal Power Flow (C-OPF) method for power system decision-mak…
Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity
Runyu Zhang, Yang Hu, Na Li
Robust Markov Decision Processes (MDPs) and risk-sensitive MDPs are both powerful tools for making decisions in the presence of uncertainties. Previous efforts have aimed to establ…
Ultra-Fine Entity Typing with Prior Knowledge about Labels: A Simple Clustering Based Strategy
Na Li, Zied Bouraoui, Steven Schockaert
Ultra-fine entity typing (UFET) is the task of inferring the semantic types, from a large set of fine-grained candidates, that apply to a given entity mention. This task is especia…
Distilling Semantic Concept Embeddings from Contrastively Fine-Tuned Language Models
Na Li, Hanane Kteich, Zied Bouraoui +1
Learning vectors that capture the meaning of concepts remains a fundamental challenge. Somewhat surprisingly, perhaps, pre-trained language models have thus far only enabled modest…
Markov Games with Decoupled Dynamics: Price of Anarchy and Sample Complexity
Runyu Zhang, Yuyang Zhang, Rohit Konda +3
This paper studies the finite-time horizon Markov games where the agents' dynamics are decoupled but the rewards can possibly be coupled across agents. The policy class is restrict…
Continuous-Time Zeroth-Order Dynamics with Projection Maps: Model-Free Feedback Optimization with Safety Guarantees
Xin Chen, Jorge I. Poveda, Na Li
This paper introduces a class of model-free feedback methods for solving generic constrained optimization problems where the specific mathematical forms of the objective and constr…
Latent Variable Representation for Reinforcement Learning
Tongzheng Ren, Chenjun Xiao, Tianjun Zhang +5
Deep latent variable models have achieved significant empirical successes in model-based reinforcement learning (RL) due to their expressiveness in modeling complex transition dyna…
Multi-Agent Reinforcement Learning with Reward Delays
Yuyang Zhang, Runyu Zhang, Yuantao Gu +1
This paper considers multi-agent reinforcement learning (MARL) where the rewards are received after delays and the delay time varies across agents and across time steps. Based on t…
On Controller Reduction in Linear Quadratic Gaussian Control with Performance Bounds
Zhaolin Ren, Yang Zheng, Maryam Fazel +1
The problem of controller reduction has a rich history in control theory. Yet, many questions remain open. In particular, there exist very few results on the order reduction of gen…
Learning to Optimize with Stochastic Dominance Constraints
Hanjun Dai, Yuan Xue, Niao He +4
In real-world decision-making, uncertainty is important yet difficult to handle. Stochastic dominance provides a theoretically sound approach for comparing uncertain quantities, bu…
Semantic Video Moments Retrieval at Scale: A New Task and a Baseline
Na Li
Motivated by the increasing need of saving search effort by obtaining relevant video clips instead of whole videos, we propose a new task, named Semantic Video Moments Retrieval at…
The DKU-Tencent System for the VoxCeleb Speaker Recognition Challenge 2022
Xiaoyi Qin, Na Li, Yuke Lin +4
This paper is the system description of the DKU-Tencent System for the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC22). In this challenge, we focus on track1 and track3. For…
Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies
Bin Hu, Kaiqing Zhang, Na Li +3
Gradient-based methods have been widely used for system design and optimization in diverse application domains. Recently, there has been a renewed interest in studying theoretical…
FedDAR: Federated Domain-Aware Representation Learning
Aoxiao Zhong, Hao He, Zhaolin Ren +2
Cross-silo Federated learning (FL) has become a promising tool in machine learning applications for healthcare. It allows hospitals/institutions to train models with sufficient dat…
On the Optimal Control of Network LQR with Spatially-Exponential Decaying Structure
Runyu Zhang, Weiyu Li, Na Li
This paper studies network LQR problems with system matrices being spatially-exponential decaying (SED) between nodes in the network. The major objective is to study whether the op…
Cross-Age Speaker Verification: Learning Age-Invariant Speaker Embeddings
Xiaoyi Qin, Na Li, Chao Weng +2
Automatic speaker verification has achieved remarkable progress in recent years. However, there is little research on cross-age speaker verification (CASV) due to insufficient rele…
Model-Free Feedback Constrained Optimization Via Projected Primal-Dual Zeroth-Order Dynamics
Xin Chen, Jorge I. Poveda, Na Li
In this paper, we propose a model-free feedback solution method to solve generic constrained optimization problems, without knowing the specific formulations of the objective and c…
A Survey on Distributed Online Optimization and Game
Xiuxian Li, Lihua Xie, Na Li
Distributed online optimization and game have been increasingly researched in the last decade, mostly motivated by its wide applications in sensor networks, robotics (e.g., distrib…
A Two-Stage Federated Transfer Learning Framework in Medical Images Classification on Limited Data: A COVID-19 Case Study
Alexandros Shikun Zhang, Naomi Fengqi Li
COVID-19 pandemic has spread rapidly and caused a shortage of global medical resources. The efficiency of COVID-19 diagnosis has become highly significant. As deep learning and con…
The CUHK-TENCENT speaker diarization system for the ICASSP 2022 multi-channel multi-party meeting transcription challenge
Naijun Zheng, Na Li, Xixin Wu +6
This paper describes our speaker diarization system submitted to the Multi-channel Multi-party Meeting Transcription (M2MeT) challenge, where Mandarin meeting data were recorded in…
On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games
Runyu Zhang, Jincheng Mei, Bo Dai +2
Softmax policy gradient is a popular algorithm for policy optimization in single-agent reinforcement learning, particularly since projection is not needed for each gradient update.…
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…
Communication-Efficient Distributed SGD with Compressed Sensing
Yujie Tang, Vikram Ramanathan, Junshan Zhang +1
We consider large scale distributed optimization over a set of edge devices connected to a central server, where the limited communication bandwidth between the server and edge dev…
Notebook-as-a-VRE (NaaVRE): from private notebooks to a collaborative cloud virtual research environment
Zhiming Zhao, Spiros Koulouzis, Riccardo Bianchi +8
Virtual Research Environments (VREs) provide user-centric support in the lifecycle of research activities, e.g., discovering and accessing research assets, or composing and executi…