b'Adish Singla'

research

∙ 07/30/2023

Evaluating ChatGPT and GPT-4 for Visual Programming

Generative AI and large language models have the potential to drasticall...

0 Adish Singla, et al. ∙

research

∙ 06/29/2023

Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutors

Generative AI and large language models hold great promise in enhancing ...

0 Tung Phung, et al. ∙

research

∙ 06/05/2023

Learning Embeddings for Sequential Tasks Using Population of Agents

We present an information-theoretic framework to learn fixed-dimensional...

0 Mridul Mahajan, et al. ∙

research

∙ 05/27/2023

Synthesizing a Progression of Subtasks for Block-Based Visual Programming Tasks

Block-based visual programming environments play an increasingly importa...

0 Alperen Tercan, et al. ∙

research

∙ 05/26/2023

Neural Task Synthesis for Visual Programming

Generative neural models hold great promise in enhancing programming edu...

0 Victor-Alexandru Pădurean, et al. ∙

research

∙ 04/25/2023

Proximal Curriculum for Reinforcement Learning Agents

We consider the problem of curriculum design for reinforcement learning ...

0 Georgios Tzannetos, et al. ∙

research

∙ 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 ...

0 Ahana Ghosh, et al. ∙

research

∙ 01/24/2023

Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models

Large language models (LLMs), such as Codex, hold great promise in enhan...

0 Tung Phung, et al. ∙

research

∙ 11/18/2022

Provable Defense against Backdoor Policies in Reinforcement Learning

We propose a provable defense mechanism against backdoor policies in rei...

0 Shubham Kumar Bharti, et al. ∙

research

∙ 06/13/2022

Specifying and Testing k-Safety Properties for Machine-Learning Models

Machine-learning models are becoming increasingly prevalent in our lives...

9 Maria Christakis, et al. ∙

research

∙ 05/04/2022

Equity and Fairness of Bayesian Knowledge Tracing

We consider the equity and fairness of curricula derived from Knowledge ...

1 Sebastian Tschiatschek, et al. ∙

research

∙ 05/03/2022

From Solution Synthesis to Student Attempt Synthesis for Block-Based Visual Programming Tasks

Block-based visual programming environments are increasingly used to int...

0 Adish Singla, et al. ∙

research

∙ 04/01/2022

Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes

Actual causality and a closely related concept of responsibility attribu...

0 Stelios Triantafyllou, et al. ∙

research

∙ 01/06/2022

Admissible Policy Teaching through Reward Design

We study reward design strategies for incentivizing a reinforcement lear...

0 Kiarash Banihashem, et al. ∙

research

∙ 10/28/2021

Teaching an Active Learner with Contrastive Examples

We study the problem of active learning with the added twist that the le...

9 Chaoqi Wang, et al. ∙

research

∙ 10/22/2021

Fairness Degrading Adversarial Attacks Against Clustering Algorithms

Clustering algorithms are ubiquitous in modern data science pipelines, a...

0 Anshuman Chhabra, et al. ∙

research

∙ 09/23/2021

Reinforcement Learning Under Algorithmic Triage

Methods to learn under algorithmic triage have predominantly focused on ...

0 Eleni Straitouri, et al. ∙

research

∙ 07/26/2021

On Blame Attribution for Accountable Multi-Agent Sequential Decision Making

Blame attribution is one of the key aspects of accountable decision maki...

0 Stelios Triantafyllou, et al. ∙

research

∙ 07/15/2021

Reinforcement Learning for Education: Opportunities and Challenges

This survey article has grown out of the RL4ED workshop organized by the...

0 Adish Singla, et al. ∙

research

∙ 06/09/2021

Bayesian Persuasion in Sequential Decision-Making

We study a dynamic model of Bayesian persuasion in sequential decision-m...

0 Jiarui Gan, et al. ∙

research

∙ 06/08/2021

Curriculum Design for Teaching via Demonstrations: Theory and Applications

We consider the problem of teaching via demonstrations in sequential dec...

0 Gaurav Yengera, et al. ∙

research

∙ 06/01/2021

Fair Clustering Using Antidote Data

Clustering algorithms are widely utilized for many modern data science a...

0 Anshuman Chhabra, et al. ∙

research

∙ 05/10/2021

Loss-Aversively Fair Classification

The use of algorithmic (learning-based) decision making in scenarios tha...

0 Junaid Ali, et al. ∙

research

∙ 02/16/2021

Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

We study black-box reward poisoning attacks against reinforcement learni...

0 Amin Rakhsha, et al. ∙

research

∙ 02/10/2021

Defense Against Reward Poisoning Attacks in Reinforcement Learning

We study defense strategies against reward poisoning attacks in reinforc...

0 Kiarash Banihashem, et al. ∙

research

∙ 11/21/2020

Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks

We study a security threat to reinforcement learning where an attacker p...

0 Amin Rakhsha, et al. ∙

research

∙ 10/17/2020

Preference-Based Batch and Sequential Teaching

Algorithmic machine teaching studies the interaction between a teacher a...

1 Farnam Mansouri, et al. ∙

research

∙ 06/25/2020

Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries

We examine the task of locating a target region among those induced by i...

4 Akash Kumar, et al. ∙

research

∙ 06/23/2020

Environment Shaping in Reinforcement Learning using State Abstraction

One of the central challenges faced by a reinforcement learning (RL) age...

0 Parameswaran Kamalaruban, et al. ∙

research

∙ 06/17/2020

Synthesizing Tasks for Block-based Programming

Block-based visual programming environments play a critical role in intr...

0 Umair Z. Ahmed, et al. ∙

research

∙ 06/16/2020

Task-agnostic Exploration in Reinforcement Learning

Efficient exploration is one of the main challenges in reinforcement lea...

0 Xuezhou Zhang, et al. ∙

research

∙ 06/16/2020

The Teaching Dimension of Q-learning

In this paper, we initiate the study of sample complexity of teaching, t...

0 Xuezhou Zhang, et al. ∙

research

∙ 03/28/2020

Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning

We study a security threat to reinforcement learning where an attacker p...

0 Amin Rakhsha, et al. ∙

research

∙ 03/27/2020

Adaptive Reward-Poisoning Attacks against Reinforcement Learning

In reward-poisoning attacks against reinforcement learning (RL), an atta...

7 Xuezhou Zhang, et al. ∙

research

∙ 03/21/2020

Understanding the Power and Limitations of Teaching with Imperfect Knowledge

Machine teaching studies the interaction between a teacher and a student...

14 Rati Devidze, et al. ∙

research

∙ 02/11/2020

Learning to Switch Between Machines and Humans

Reinforcement learning algorithms have been mostly developed and evaluat...

0 Vahid Balazadeh-Meresht, et al. ∙

research

∙ 10/24/2019

Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models

Algorithmic machine teaching studies the interaction between a teacher a...

0 Farnam Mansouri, et al. ∙

research

∙ 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 ...

0 Ahana Ghosh, et al. ∙

research

∙ 09/01/2019

Can A User Guess What Her Followers Want?

Whenever a social media user decides to share a story, she is typically ...

0 Abir De, et al. ∙

research

∙ 06/02/2019

Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints

Inverse reinforcement learning (IRL) enables an agent to learn complex b...

0 Sebastian Tschiatschek, et al. ∙

research

∙ 05/28/2019

Interactive Teaching Algorithms for Inverse Reinforcement Learning

We study the problem of inverse reinforcement learning (IRL) with the ad...

0 Parameswaran Kamalaruban, et al. ∙

research

∙ 05/22/2019

Optimal Decision Making Under Strategic Behavior

We are witnessing an increasing use of data-driven predictive models to ...

5 Moein Khajehnejad, et al. ∙

research

∙ 05/16/2019

On the Fairness of Time-Critical Influence Maximization in Social Networks

Influence maximization has found applications in a wide range of real-wo...

0 Junaid Ali, et al. ∙

research

∙ 02/27/2019

Unifying Ensemble Methods for Q-learning via Social Choice Theory

Ensemble methods have been widely applied in Reinforcement Learning (RL)...

0 Rishav Chourasia, et al. ∙

research

∙ 01/23/2019

Learning to Collaborate in Markov Decision Processes

We consider a two-agent MDP framework where agents repeatedly solve a ta...

0 Goran Radanovic, et al. ∙

research

∙ 12/11/2018

Efficient learning of smooth probability functions from Bernoulli tests with guarantees

We study the fundamental problem of learning an unknown, smooth probabil...

0 Paul Rolland, et al. ∙

research

∙ 11/08/2018

Iterative Classroom Teaching

We consider the machine teaching problem in a classroom-like setting whe...

1 Teresa Yeo, et al. ∙

research

∙ 10/21/2018

Teaching Inverse Reinforcement Learners via Features and Demonstrations

Learning near-optimal behaviour from an expert's demonstrations typicall...

0 Luis Haug, et al. ∙

research

∙ 07/02/2018

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices

Discrimination via algorithmic decision making has received considerable...

0 Till Speicher, et al. ∙

research

∙ 05/25/2018

Enhancing the Accuracy and Fairness of Human Decision Making

Societies often rely on human experts to take a wide variety of decision...

0 Isabel Valera, et al. ∙

Adish Singla

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