Search Results for author: He Bai

Found 29 papers, 8 papers with code

Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation

no code implementations20 Sep 2023 Ali Mousavi, Xin Zhan, He Bai, Peng Shi, Theo Rekatsinas, Benjamin Han, Yunyao Li, Jeff Pound, Josh Susskind, Natalie Schluter, Ihab Ilyas, Navdeep Jaitly

Guided by these observations, we construct a new, improved dataset called LAGRANGE using heuristics meant to improve equivalence between KG and text and show the impact of each of the heuristics on cyclic evaluation.

Knowledge Graphs

Asynchronous Bayesian Learning over a Network

no code implementations16 Nov 2022 Kinjal Bhar, He Bai, Jemin George, Carl Busart

We present a practical asynchronous data fusion model for networked agents to perform distributed Bayesian learning without sharing raw data.

ERNIE-SAT: Speech and Text Joint Pretraining for Cross-Lingual Multi-Speaker Text-to-Speech

2 code implementations7 Nov 2022 Xiaoran Fan, Chao Pang, Tian Yuan, He Bai, Renjie Zheng, Pengfei Zhu, Shuohuan Wang, Junkun Chen, Zeyu Chen, Liang Huang, Yu Sun, Hua Wu

In this paper, we extend the pretraining method for cross-lingual multi-speaker speech synthesis tasks, including cross-lingual multi-speaker voice cloning and cross-lingual multi-speaker speech editing.

Representation Learning Speech Synthesis +2

XRICL: Cross-lingual Retrieval-Augmented In-Context Learning for Cross-lingual Text-to-SQL Semantic Parsing

no code implementations25 Oct 2022 Peng Shi, Rui Zhang, He Bai, Jimmy Lin

We also include global translation exemplars for a target language to facilitate the translation process for large language models.

Retrieval Semantic Parsing +3

Better Language Model with Hypernym Class Prediction

1 code implementation ACL 2022 He Bai, Tong Wang, Alessandro Sordoni, Peng Shi

Class-based language models (LMs) have been long devised to address context sparsity in $n$-gram LMs.

Language Modelling

A$^3$T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and Editing

2 code implementations18 Mar 2022 He Bai, Renjie Zheng, Junkun Chen, Xintong Li, Mingbo Ma, Liang Huang

Recently, speech representation learning has improved many speech-related tasks such as speech recognition, speech classification, and speech-to-text translation.

Representation Learning Speaker Verification +5

Distributed Multi-Agent Reinforcement Learning Based on Graph-Induced Local Value-Functions

no code implementations26 Feb 2022 Gangshan Jing, He Bai, Jemin George, Aranya Chakrabortty, Piyush K. Sharma

Achieving distributed reinforcement learning (RL) for large-scale cooperative multi-agent systems (MASs) is challenging because: (i) each agent has access to only limited information; (ii) issues on convergence or computational complexity emerge due to the curse of dimensionality.

Multi-agent Reinforcement Learning reinforcement-learning +1

Distributed Cooperative Multi-Agent Reinforcement Learning with Directed Coordination Graph

no code implementations10 Jan 2022 Gangshan Jing, He Bai, Jemin George, Aranya Chakrabortty, Piyush. K. Sharma

In this work, we study MARLs with directed coordination graphs, and propose a distributed RL algorithm where the local policy evaluations are based on local value functions.

Multi-agent Reinforcement Learning reinforcement-learning +1

Variance Reduction of Quadcopter Trajectory Tracking in Turbulent Wind

no code implementations20 Apr 2021 Asma Tabassum, Rohit K. S. S. Vuppala, He Bai, Kursat Kara

In particular, we design a minimum cost variance (MCV) controller aiming to minimize the cost in terms of its weighted sum of mean and variance.

Dynamic Control Allocation between Onboard and Delayed Remote Control for Unmanned Aircraft System Detect-and-Avoid

no code implementations14 Mar 2021 Asma Tabassum, He Bai

We consider a UAS that can be fully controlled by the onboard DAA system and by a remote human pilot.

Decentralized Langevin Dynamics for Bayesian Learning

no code implementations NeurIPS 2020 Anjaly Parayil, He Bai, Jemin George, Prudhvi Gurram

Motivated by decentralized approaches to machine learning, we propose a collaborative Bayesian learning algorithm taking the form of decentralized Langevin dynamics in a non-convex setting.

BIG-bench Machine Learning

Online Observer-Based Inverse Reinforcement Learning

no code implementations3 Nov 2020 Ryan Self, Kevin Coleman, He Bai, Rushikesh Kamalapurkar

In this paper, a novel approach to the output-feedback inverse reinforcement learning (IRL) problem is developed by casting the IRL problem, for linear systems with quadratic cost functions, as a state estimation problem.

reinforcement-learning Reinforcement Learning (RL)

Cross-Lingual Training of Neural Models for Document Ranking

no code implementations Findings of the Association for Computational Linguistics 2020 Peng Shi, He Bai, Jimmy Lin

We tackle the challenge of cross-lingual training of neural document ranking models for mono-lingual retrieval, specifically leveraging relevance judgments in English to improve search in non-English languages.

Document Ranking Retrieval

Decomposability and Parallel Computation of Multi-Agent LQR

no code implementations16 Oct 2020 Gangshan Jing, He Bai, Jemin George, Aranya Chakrabortty

Conditions for decomposability, an algorithm for constructing the transformation matrix, a parallel RL algorithm, and robustness analysis when the design is applied to non-homogeneous MAS are presented.

Hierarchical Reinforcement Learning Reinforcement Learning (RL)

Model-Free Optimal Control of Linear Multi-Agent Systems via Decomposition and Hierarchical Approximation

no code implementations14 Aug 2020 Gangshan Jing, He Bai, Jemin George, Aranya Chakrabortty

The first component optimizes the performance of each independent cluster by solving the smaller-size LQR design problem in a model-free way using an RL algorithm.

Clustering Graph Clustering +1

A Decentralized Approach to Bayesian Learning

1 code implementation14 Jul 2020 Anjaly Parayil, He Bai, Jemin George, Prudhvi Gurram

Motivated by decentralized approaches to machine learning, we propose a collaborative Bayesian learning algorithm taking the form of decentralized Langevin dynamics in a non-convex setting.

BIG-bench Machine Learning

Emulating UAV Motion by Utilizing Robotic Arm for mmWave Wireless Channel Characterization

1 code implementation20 Jun 2020 Amit Kachroo, Collin A. Thornton, Md Arifur Rahman Sarker, Wooyeol Choi, He Bai, Ickhyun Song, John O'Hara, Sabit Ekin

In this paper, millimeter wave (mmWave) wireless channel characteristics (Doppler spread and path loss modeling) for Unmanned Aerial Vehicles (UAVs) assisted communication is analyzed and studied by emulating the real UAV motion using a robotic arm.

Segatron: Segment-Aware Transformer for Language Modeling and Understanding

1 code implementation30 Apr 2020 He Bai, Peng Shi, Jimmy Lin, Yuqing Xie, Luchen Tan, Kun Xiong, Wen Gao, Ming Li

To verify this, we propose a segment-aware Transformer (Segatron), by replacing the original token position encoding with a combined position encoding of paragraph, sentence, and token.

Language Modelling Masked Language Modeling +1

Reduced-Dimensional Reinforcement Learning Control using Singular Perturbation Approximations

no code implementations29 Apr 2020 Sayak Mukherjee, He Bai, Aranya Chakrabortty

We present a set of model-free, reduced-dimensional reinforcement learning (RL) based optimal control designs for linear time-invariant singularly perturbed (SP) systems.

Clustering reinforcement-learning +1

Distributed Stochastic Gradient Method for Non-Convex Problems with Applications in Supervised Learning

1 code implementation19 Aug 2019 Jemin George, Tao Yang, He Bai, Prudhvi Gurram

Numerical results also show that the proposed distributed algorithm allows the individual agents to recognize the digits even though the training data corresponding to all the digits is not locally available to each agent.

Optimization and Control Systems and Control Systems and Control

Wind Estimation Using Quadcopter Motion: A Machine Learning Approach

no code implementations11 Jul 2019 Sam Allison, He Bai, Balaji Jayaraman

In this article, we study the well known problem of wind estimation in atmospheric turbulence using small unmanned aerial systems (sUAS).

Autonomous Navigation BIG-bench Machine Learning

Memory Consolidation for Contextual Spoken Language Understanding with Dialogue Logistic Inference

no code implementations ACL 2019 He Bai, Yu Zhou, Jiajun Zhang, Cheng-qing Zong

Dialogue contexts are proven helpful in the spoken language understanding (SLU) system and they are typically encoded with explicit memory representations.

Retrieval slot-filling +2

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