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05/26/2023
Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making
We argue that explanations for "algorithmic decision-making" (ADM) syste...
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05/25/2023
Learning Safety Constraints from Demonstrations with Unknown Rewards
We propose Convex Constraint Learning for Reinforcement Learning (CoCoRL...
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03/28/2023
Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes
Block-based programming environments are increasingly used to introduce ...
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02/16/2023
On the Impact of Explanations on Understanding of Algorithmic Decision-Making
Ethical principles for algorithms are gaining importance as more and mor...
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06/10/2022
Interactively Learning Preference Constraints in Linear Bandits
We study sequential decision-making with known rewards and unknown const...
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05/04/2022
Equity and Fairness of Bayesian Knowledge Tracing
We consider the equity and fairness of curricula derived from Knowledge ...
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10/18/2021
MDP Abstraction with Successor Features
Abstraction plays an important role for generalisation of knowledge and ...
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02/24/2021
Information Directed Reward Learning for Reinforcement Learning
For many reinforcement learning (RL) applications, specifying a reward i...
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11/02/2020
Reinforcement Learning with Efficient Active Feature Acquisition
Solving real-life sequential decision making problems under partial obse...
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06/25/2020
Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces
The ever-increasing take-up of machine learning techniques requires ever...
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06/21/2020
VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data
Deep generative models often perform poorly in real-world applications d...
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03/12/2020
Large-Scale Educational Question Analysis with Partial Variational Auto-encoders
Online education platforms enable teachers to share a large number of ed...
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01/07/2020
Resource-Efficient Neural Networks for Embedded Systems
While machine learning is traditionally a resource intensive task, embed...
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11/08/2019
Collaborative Machine Learning Markets with Data-Replication-Robust Payments
We study the problem of collaborative machine learning markets where mul...
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10/28/2019
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
The ability for policies to generalize to new environments is key to the...
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10/05/2019
Towards Deployment of Robust AI Agents for Human-Machine Partnerships
We study the problem of designing AI agents that can robustly cooperate ...
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08/13/2019
Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model
In this paper we introduce the ice-start problem, i.e., the challenge of...
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06/02/2019
Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
Inverse reinforcement learning (IRL) enables an agent to learn complex b...
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12/05/2018
Efficient and Robust Machine Learning for Real-World Systems
While machine learning is traditionally a resource intensive task, embed...
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10/21/2018
Teaching Inverse Reinforcement Learners via Features and Demonstrations
Learning near-optimal behaviour from an expert's demonstrations typicall...
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10/15/2018
Successor Uncertainties: exploration and uncertainty in temporal difference learning
We consider the problem of balancing exploration and exploitation in seq...
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09/28/2018
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
Making decisions requires information relevant to the task at hand. Many...
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07/06/2018
Sum-Product Networks for Sequence Labeling
We consider higher-order linear-chain conditional random fields (HO-LC-C...
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05/23/2018
Variational Inference for Data-Efficient Model Learning in POMDPs
Partially observable Markov decision processes (POMDPs) are a powerful a...
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03/05/2018
Differentiable Submodular Maximization
We consider learning of submodular functions from data. These functions ...
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11/17/2017
Learning User Preferences to Incentivize Exploration in the Sharing Economy
We study platforms in the sharing economy and discuss the need for incen...
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02/09/2017
Coordinated Online Learning With Applications to Learning User Preferences
We study an online multi-task learning setting, in which instances of re...
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05/23/2016
Actively Learning Hemimetrics with Applications to Eliciting User Preferences
Motivated by an application of eliciting users' preferences, we investig...
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11/23/2015