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07/07/2023
TRAC: Trustworthy Retrieval Augmented Chatbot
Although conversational AIs have demonstrated fantastic performance, the...
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05/26/2023
Policy Synthesis and Reinforcement Learning for Discounted LTL
The difficulty of manually specifying reward functions has led to an int...
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05/22/2023
TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching
Standard model-based reinforcement learning (MBRL) approaches fit a tran...
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03/28/2023
Ideograph: A Language for Expressing and Manipulating Structured Data
We introduce Ideograph, a language for expressing and manipulating struc...
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02/17/2023
PAC Prediction Sets for Large Language Models of Code
Prediction sets have recently been shown to be a promising strategy for ...
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02/06/2023
Robust Subtask Learning for Compositional Generalization
Compositional reinforcement learning is a promising approach for trainin...
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02/03/2023
SPARLING: Learning Latent Representations with Extremely Sparse Activations
Real-world processes often contain intermediate state that can be modele...
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11/17/2022
ACon^2: Adaptive Conformal Consensus for Provable Blockchain Oracles
Blockchains with smart contracts are distributed ledger systems which ac...
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11/15/2022
Decision-Aware Learning for Optimizing Health Supply Chains
We study the problem of allocating limited supply of medical resources i...
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11/11/2022
Bandits for Online Calibration: An Application to Content Moderation on Social Media Platforms
We describe the current content moderation strategy employed by Meta to ...
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07/06/2022
PAC Prediction Sets for Meta-Learning
Uncertainty quantification is a key component of machine learning models...
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06/07/2022
How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression
Offline goal-conditioned reinforcement learning (GCRL) promises general-...
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06/06/2022
Specification-Guided Learning of Nash Equilibria with High Social Welfare
Reinforcement learning has been shown to be an effective strategy for au...
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06/02/2022
Practical Adversarial Multivalid Conformal Prediction
We give a simple, generic conformal prediction method for sequential pre...
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04/27/2022
Counterfactual Explanations for Natural Language Interfaces
A key challenge facing natural language interfaces is enabling users to ...
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04/15/2022
Towards PAC Multi-Object Detection and Tracking
Accurately detecting and tracking multi-objects is important for safety-...
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02/25/2022
Exploring with Sticky Mittens: Reinforcement Learning with Expert Interventions via Option Templates
Environments with sparse rewards and long horizons pose a significant ch...
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02/20/2022
Understanding Robust Generalization in Learning Regular Languages
A key feature of human intelligence is the ability to generalize beyond ...
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02/04/2022
SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching
We propose State Matching Offline DIstribution Correction Estimation (SM...
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12/14/2021
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning
Reinforcement Learning (RL) agents in the real world must satisfy safety...
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10/25/2021
Safely Bridging Offline and Online Reinforcement Learning
A key challenge to deploying reinforcement learning in practice is explo...
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10/11/2021
Safe Human-Interactive Control via Shielding
Ensuring safety for human-interactive robotics is important due to the p...
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10/11/2021
Synthesizing Machine Learning Programs with PAC Guarantees via Statistical Sketching
We study the problem of synthesizing programs that include machine learn...
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09/22/2021
Robust Generalization of Quadratic Neural Networks via Function Identification
A key challenge facing deep learning is that neural networks are often n...
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08/19/2021
Improving Human Decision-Making with Machine Learning
A key aspect of human intelligence is their ability to convey their know...
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07/12/2021
Conservative Offline Distributional Reinforcement Learning
Many reinforcement learning (RL) problems in practice are offline, learn...
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06/25/2021
Compositional Reinforcement Learning from Logical Specifications
We study the problem of learning control policies for complex tasks give...
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06/17/2021
PAC Prediction Sets Under Covariate Shift
An important challenge facing modern machine learning is how to rigorous...
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04/18/2021
Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings
Sparse regression has recently been applied to enable transfer learning ...
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04/14/2021
Web Question Answering with Neurosymbolic Program Synthesis
In this paper, we propose a new technique based on program synthesis for...
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03/26/2021
SkyQuery: An Aerial Drone Video Sensing Platform
Video-based sensing from aerial drones, especially small multirotor dron...
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02/22/2021
Program Synthesis Guided Reinforcement Learning
A key challenge for reinforcement learning is solving long-horizon plann...
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01/05/2021
Neurosymbolic Transformers for Multi-Agent Communication
We study the problem of inferring communication structures that can solv...
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11/30/2020
Diverse Sampling for Normalizing Flow Based Trajectory Forecasting
For autonomous cars to drive safely and effectively, they must anticipat...
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11/12/2020
Robust and Stable Black Box Explanations
As machine learning black boxes are increasingly being deployed in real-...
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11/12/2020
Ensuring Actionable Recourse via Adversarial Training
As machine learning models are increasingly deployed in high-stakes doma...
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11/02/2020
PAC Confidence Predictions for Deep Neural Network Classifiers
A key challenge for deploying deep neural networks (DNNs) in safety crit...
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10/29/2020
Abstract Value Iteration for Hierarchical Reinforcement Learning
We propose a novel hierarchical reinforcement learning framework for con...
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08/21/2020
A Composable Specification Language for Reinforcement Learning Tasks
Reinforcement learning is a promising approach for learning control poli...
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02/29/2020
Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation
Reliable uncertainty estimates are an important tool for helping autonom...
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12/31/2019
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
We propose an algorithm combining calibrated prediction and generalizati...
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12/29/2019
Synthesizing Queries via Interactive Sketching
We propose a novel approach to program synthesis, focusing on synthesizi...
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11/15/2019
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations
As machine learning black boxes are increasingly being deployed in criti...
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10/25/2019
MAMPS: Safe Multi-Agent Reinforcement Learning via Model Predictive Shielding
Reinforcement learning is a promising approach to learning control polic...
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10/24/2019
Robust Model Predictive Shielding for Safe Reinforcement Learning with Stochastic Dynamics
This paper proposes a framework for safe reinforcement learning that can...
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07/11/2019
Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints
In this paper, we present a learning approach to goal assignment and tra...
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05/25/2019
Safe Reinforcement Learning via Online Shielding
Reinforcement learning is a promising approach to learning control polic...
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02/25/2019
PolyDroid: Learning-Driven Specialization of Mobile Applications
The increasing prevalence of mobile apps has led to a proliferation of r...
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01/24/2019
Learning Interpretable Models with Causal Guarantees
Machine learning has shown much promise in helping improve the quality o...
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01/24/2019
