research
∙
08/20/2023
Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi
Cooperative Multi-agent Reinforcement Learning (MARL) algorithms with Ze...
share
research
∙
05/06/2023
Listen to Look into the Future: Audio-Visual Egocentric Gaze Anticipation
Egocentric gaze anticipation serves as a key building block for the emer...
research
∙
03/30/2023
Learning in Factored Domains with Information-Constrained Visual Representations
Humans learn quickly even in tasks that contain complex visual informati...
research
∙
02/06/2023
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
Due to the significant computational challenge of training large-scale g...
research
∙
12/16/2022
Werewolf Among Us: A Multimodal Dataset for Modeling Persuasion Behaviors in Social Deduction Games
Persuasion modeling is a key building block for conversational agents. E...
research
∙
10/28/2022
Game-Theoretical Perspectives on Active Equilibria: A Preferred Solution Concept over Nash Equilibria
Multiagent learning settings are inherently more difficult than single-a...
research
∙
10/23/2022
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach
Machine learning problems with multiple objective functions appear eithe...
research
∙
08/08/2022
In the Eye of Transformer: Global-Local Correlation for Egocentric Gaze Estimation
In this paper, we present the first transformer-based model to address t...
research
∙
03/21/2022
Generative Adversarial Network for Future Hand Segmentation from Egocentric Video
We introduce the novel problem of anticipating a time series of future h...
research
∙
03/07/2022
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
The main challenge of multiagent reinforcement learning is the difficult...
research
∙
03/01/2022
AI Planning Annotation for Sample Efficient Reinforcement Learning
AI planning and Reinforcement Learning (RL) both solve sequential decisi...
research
∙
02/16/2022
An efficient distributed scheduling algorithm for relay-assisted mmWave backhaul networks
In this paper, a novel distributed scheduling algorithm is proposed, whi...
research
∙
02/11/2022
Towards the Maximum Traffic Demand and Throughput Supported by Relay-Assisted mmWave Backhaul Networks
This paper investigates the throughput performance issue of the relay-as...
research
∙
02/08/2022
Local Explanations for Reinforcement Learning
Many works in explainable AI have focused on explaining black-box classi...
research
∙
09/20/2021
Context-Specific Representation Abstraction for Deep Option Learning
Hierarchical reinforcement learning has focused on discovering temporall...
research
∙
05/20/2021
Egocentric Activity Recognition and Localization on a 3D Map
Given a video captured from a first person perspective and recorded in a...
research
∙
11/26/2020
4D Human Body Capture from Egocentric Video via 3D Scene Grounding
To understand human daily social interaction from egocentric perspective...
research
∙
11/23/2020
Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games
This paper introduces an information-theoretic constraint on learned pol...
research
∙
10/31/2020
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
A fundamental challenge in multiagent reinforcement learning is to learn...
research
∙
10/09/2020
Deep RL With Information Constrained Policies: Generalization in Continuous Control
Biological agents learn and act intelligently in spite of a highly limit...
research
∙
05/31/2020
In the Eye of the Beholder: Gaze and Actions in First Person Video
We address the task of jointly determining what a person is doing and wh...
research
∙
01/24/2020
Characterization and Thermal Management of a DC Motor-Driven Resonant Actuator for Miniature Mobile Robots with Oscillating Limbs
In this paper, we characterize the performance of and develop thermal ma...
research
∙
12/31/2019
On the Role of Weight Sharing During Deep Option Learning
The options framework is a popular approach for building temporally exte...
research
∙
11/25/2019
Forecasting Human Object Interaction: Joint Prediction of Motor Attention and Egocentric Activity
We address the challenging task of anticipating human-object interaction...
research
∙
04/05/2019
Paying More Attention to Motion: Attention Distillation for Learning Video Representations
We address the challenging problem of learning motion representations us...
research
∙
03/07/2019
Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning
Heterogeneous knowledge naturally arises among different agents in coope...
research
∙
10/29/2018
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference
Lack of performance when it comes to continual learning over non-station...
research
∙
10/27/2018
Learning Abstract Options
Building systems that autonomously create temporal abstractions from dat...
research
∙
10/09/2018
Evaluating the Effectiveness of Health Awareness Events by Google Search Frequency
Over two hundreds health awareness events take place in the United State...
research
∙
05/20/2018
Learning to Teach in Cooperative Multiagent Reinforcement Learning
We present a framework and algorithm for peer-to-peer teaching in cooper...
research
∙
12/11/2017
The Eigenoption-Critic Framework
Eigenoptions (EOs) have been recently introduced as a promising idea for...
research
∙
10/30/2017
Eigenoption Discovery through the Deep Successor Representation
Options in reinforcement learning allow agents to hierarchically decompo...
research
∙
07/24/2017
Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions
This paper presents a data-driven approach for multi-robot coordination ...
research
∙
03/16/2017
Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces
This paper presents the first ever approach for solving continuous-obser...
research
∙
03/16/2017
Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations
Robust environment perception is essential for decision-making on robots...
research
∙
05/01/2015
Stick-Breaking Policy Learning in Dec-POMDPs
Expectation maximization (EM) has recently been shown to be an efficient...
research
∙
05/28/2013
