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01/04/2023
Multi-Task Learning for Budbreak Prediction
Grapevine budbreak is a key phenological stage of seasonal development, ...
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09/22/2022
Oracle Analysis of Representations for Deep Open Set Detection
The problem of detecting a novel class at run time is known as Open Set ...
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09/21/2022
Grape Cold Hardiness Prediction via Multi-Task Learning
Cold temperatures during fall and spring have the potential to cause fro...
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07/16/2022
Dynamic Bipedal Maneuvers through Sim-to-Real Reinforcement Learning
For legged robots to match the athletic capabilities of humans and anima...
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07/09/2022
Optimizing Bipedal Maneuvers of Single Rigid-Body Models for Reinforcement Learning
In this work, we propose a method to generate reduced-order model refere...
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06/04/2022
Beyond Value: CHECKLIST for Testing Inferences in Planning-Based RL
Reinforcement learning (RL) agents are commonly evaluated via their expe...
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05/22/2022
Offline Policy Comparison with Confidence: Benchmarks and Baselines
Decision makers often wish to use offline historical data to compare seq...
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05/03/2022
Learning Dynamic Bipedal Walking Across Stepping Stones
In this work, we propose a learning approach for 3D dynamic bipedal walk...
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04/09/2022
Sim-to-Real Learning for Bipedal Locomotion Under Unsensed Dynamic Loads
Recent work on sim-to-real learning for bipedal locomotion has demonstra...
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03/15/2022
Sim-to-Real Learning of Footstep-Constrained Bipedal Dynamic Walking
Recently, work on reinforcement learning (RL) for bipedal robots has suc...
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09/28/2021
Identifying Reasoning Flaws in Planning-Based RL Using Tree Explanations
Enabling humans to identify potential flaws in an agent's decision makin...
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09/13/2021
From Heatmaps to Structural Explanations of Image Classifiers
This paper summarizes our endeavors in the past few years in terms of ex...
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07/11/2021
Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and Results
We study the problem of out-of-distribution dynamics (OODD) detection, w...
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06/11/2021
Piecewise-constant Neural ODEs
Neural networks are a popular tool for modeling sequential data but they...
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05/18/2021
Blind Bipedal Stair Traversal via Sim-to-Real Reinforcement Learning
Accurate and precise terrain estimation is a difficult problem for robot...
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05/01/2021
Deep Convolution for Irregularly Sampled Temporal Point Clouds
We consider the problem of modeling the dynamics of continuous spatial-t...
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12/14/2020
Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework
We consider the problem of optimizing expensive black-box functions over...
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11/13/2020
Structured Attention Graphs for Understanding Deep Image Classifications
Attention maps are a popular way of explaining the decisions of convolut...
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11/09/2020
Learning Task Space Actions for Bipedal Locomotion
Recent work has demonstrated the success of reinforcement learning (RL) ...
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11/02/2020
Sim-to-Real Learning of All Common Bipedal Gaits via Periodic Reward Composition
We study the problem of realizing the full spectrum of bipedal locomotio...
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10/21/2020
Learning Spring Mass Locomotion: Guiding Policies with a Reduced-Order Model
In this paper, we describe an approach to achieve dynamic legged locomot...
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10/19/2020
Dream and Search to Control: Latent Space Planning for Continuous Control
Learning and planning with latent space dynamics has been shown to be us...
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10/18/2020
DeepAveragers: Offline Reinforcement Learning by Solving Derived Non-Parametric MDPs
We study an approach to offline reinforcement learning (RL) based on opt...
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10/11/2020
Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
We investigate a deep reinforcement learning (RL) architecture that supp...
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06/06/2020
Understanding Finite-State Representations of Recurrent Policy Networks
We introduce an approach for understanding finite-state machine (FSM) re...
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06/03/2020
Learning Memory-Based Control for Human-Scale Bipedal Locomotion
Controlling a non-statically stable biped is a difficult problem largely...
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10/01/2019
The Choice Function Framework for Online Policy Improvement
There are notable examples of online search improving over hand-coded or...
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03/22/2019
Explaining Reinforcement Learning to Mere Mortals: An Empirical Study
We present a user study to investigate the impact of explanations on non...
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12/18/2018
Interactive Naming for Explaining Deep Neural Networks: A Formative Study
We consider the problem of explaining the decisions of deep neural netwo...
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11/29/2018
Learning Finite State Representations of Recurrent Policy Networks
Recurrent neural networks (RNNs) are an effective representation of cont...
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08/01/2018
Open Category Detection with PAC Guarantees
Open category detection is the problem of detecting "alien" test instanc...
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10/31/2017
Visualizing and Understanding Atari Agents
Deep reinforcement learning (deep RL) agents have achieved remarkable su...
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10/03/2017
AutoMode: Relational Learning With Less Black Magic
Relational databases are valuable resources for learning novel and inter...
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08/30/2017
Incorporating Feedback into Tree-based Anomaly Detection
Anomaly detectors are often used to produce a ranked list of statistical...
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07/26/2016
Approximate Policy Iteration for Budgeted Semantic Video Segmentation
This paper formulates and presents a solution to the new problem of budg...
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08/16/2015
Schema Independent Relational Learning
Learning novel concepts and relations from relational databases is an im...
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03/03/2015
A Meta-Analysis of the Anomaly Detection Problem
This article provides a thorough meta-analysis of the anomaly detection ...
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02/28/2015
Sequential Feature Explanations for Anomaly Detection
In many applications, an anomaly detection system presents the most anom...
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12/12/2012
Inductive Policy Selection for First-Order MDPs
We select policies for large Markov Decision Processes (MDPs) with compa...
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10/16/2012
Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games
In typical real-time strategy (RTS) games, enemy units are visible only ...
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10/16/2012
Active Imitation Learning via Reduction to I.I.D. Active Learning
In standard passive imitation learning, the goal is to learn a target po...
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06/27/2012
Output Space Search for Structured Prediction
We consider a framework for structured prediction based on search in the...
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06/27/2012
