activity
20152026
most citedAn Overview of Machine Teaching

102 citations · 254 across the 55 of their papers we have counts for

collaborators
Showing 2020Show all

11 papers · 1 filter

cs.LG20208 cited

Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks

Amin Rakhsha, Goran Radanovic, Rati Devidze +2

We study a security threat to reinforcement learning where an attacker poisons the learning environment to force the agent into executing a target policy chosen by the attacker. As…

cs.LG2020

Preference-Based Batch and Sequential Teaching

Farnam Mansouri, Yuxin Chen, Ara Vartanian +2

Algorithmic machine teaching studies the interaction between a teacher and a learner where the teacher selects labeled examples aiming at teaching a target hypothesis. In a quest t…

cs.LG2020

The Teaching Dimension of Kernel Perceptron

Akash Kumar, Hanqi Zhang, Adish Singla +1

Algorithmic machine teaching has been studied under the linear setting where exact teaching is possible. However, little is known for teaching nonlinear learners. Here, we establis…

cs.LG2020

Environment Shaping in Reinforcement Learning using State Abstraction

Parameswaran Kamalaruban, Rati Devidze, Volkan Cevher +1

One of the central challenges faced by a reinforcement learning (RL) agent is to effectively learn a (near-)optimal policy in environments with large state spaces having sparse and…

cs.LG202013 cited

Task-agnostic Exploration in Reinforcement Learning

Xuezhou Zhang, Yuzhe ma, Adish Singla

Efficient exploration is one of the main challenges in reinforcement learning (RL). Most existing sample-efficient algorithms assume the existence of a single reward function durin…

cs.CY2020

Synthesizing Tasks for Block-based Programming

Umair Z. Ahmed, Maria Christakis, Aleksandr Efremov +4

Block-based visual programming environments play a critical role in introducing computing concepts to K-12 students. One of the key pedagogical challenges in these environments is…