Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Amos Azaria

Amos Azaria

Explaining Ridesharing: Selection of Explanations for Increasing User Satisfaction


May 26, 2021
David Zar, Noam Hazon, Amos Azaria

Figure 1 for Explaining Ridesharing: Selection of Explanations for Increasing User Satisfaction
Figure 2 for Explaining Ridesharing: Selection of Explanations for Increasing User Satisfaction
Figure 3 for Explaining Ridesharing: Selection of Explanations for Increasing User Satisfaction
Figure 4 for Explaining Ridesharing: Selection of Explanations for Increasing User Satisfaction
* 19 pages, 4 figures 
  Access Paper or Ask Questions

Conversational Neuro-Symbolic Commonsense Reasoning


Jun 19, 2020
Forough Arabshahi, Jennifer Lee, Mikayla Gawarecki, Kathryn Mazaitis, Amos Azaria, Tom Mitchell

Figure 1 for Conversational Neuro-Symbolic Commonsense Reasoning
Figure 2 for Conversational Neuro-Symbolic Commonsense Reasoning
Figure 3 for Conversational Neuro-Symbolic Commonsense Reasoning
Figure 4 for Conversational Neuro-Symbolic Commonsense Reasoning

  Access Paper or Ask Questions

Fiction Sentence Expansion and Enhancement via Focused Objective and Novelty Curve Sampling


Dec 03, 2019
Yuri Safovich, Amos Azaria

Figure 1 for Fiction Sentence Expansion and Enhancement via Focused Objective and Novelty Curve Sampling
Figure 2 for Fiction Sentence Expansion and Enhancement via Focused Objective and Novelty Curve Sampling
Figure 3 for Fiction Sentence Expansion and Enhancement via Focused Objective and Novelty Curve Sampling
Figure 4 for Fiction Sentence Expansion and Enhancement via Focused Objective and Novelty Curve Sampling

  Access Paper or Ask Questions

AI for Explaining Decisions in Multi-Agent Environments


Oct 12, 2019
Sarit Kraus, Amos Azaria, Jelena Fiosina, Maike Greve, Noam Hazon, Lutz Kolbe, Tim-Benjamin Lembcke, Jörg P. Müller, Sören Schleibaum, Mark Vollrath

Figure 1 for AI for Explaining Decisions in Multi-Agent Environments
* This paper has been submitted to the Blue Sky Track of the AAAI 2020 conference. At the time of submission, it is under review. The tentative notification date will be November 10, 2019. Current version: Name of first author had been added in metadata 
  Access Paper or Ask Questions

Learning to Conceal: A Deep Learning Based Method for Preserving Privacy and Avoiding Prejudice


Sep 19, 2019
Moshe Hanukoglu, Nissan Goldberg, Aviv Rovshitz, Amos Azaria

Figure 1 for Learning to Conceal: A Deep Learning Based Method for Preserving Privacy and Avoiding Prejudice
Figure 2 for Learning to Conceal: A Deep Learning Based Method for Preserving Privacy and Avoiding Prejudice
Figure 3 for Learning to Conceal: A Deep Learning Based Method for Preserving Privacy and Avoiding Prejudice
Figure 4 for Learning to Conceal: A Deep Learning Based Method for Preserving Privacy and Avoiding Prejudice

  Access Paper or Ask Questions

InstructableCrowd: Creating IF-THEN Rules for Smartphones via Conversations with the Crowd


Sep 12, 2019
Ting-Hao 'Kenneth' Huang, Amos Azaria, Oscar J. Romero, Jeffrey P. Bigham

Figure 1 for InstructableCrowd: Creating IF-THEN Rules for Smartphones via Conversations with the Crowd
Figure 2 for InstructableCrowd: Creating IF-THEN Rules for Smartphones via Conversations with the Crowd
Figure 3 for InstructableCrowd: Creating IF-THEN Rules for Smartphones via Conversations with the Crowd
Figure 4 for InstructableCrowd: Creating IF-THEN Rules for Smartphones via Conversations with the Crowd
* Human Computation (2019) 6:1:113-146 
 * Published at Human Computation (2019) 6:1:113-146 
  Access Paper or Ask Questions

Deep Reinforcement Learning for Time Optimal Velocity Control using Prior Knowledge


Mar 12, 2019
Gabriel Hartmann, Zvi Shiller, Amos Azaria

Figure 1 for Deep Reinforcement Learning for Time Optimal Velocity Control using Prior Knowledge
Figure 2 for Deep Reinforcement Learning for Time Optimal Velocity Control using Prior Knowledge
Figure 3 for Deep Reinforcement Learning for Time Optimal Velocity Control using Prior Knowledge
Figure 4 for Deep Reinforcement Learning for Time Optimal Velocity Control using Prior Knowledge

  Access Paper or Ask Questions

Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds


Feb 25, 2019
Igor Labutov, Bishan Yang, Anusha Prakash, Amos Azaria

Figure 1 for Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds
Figure 2 for Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds
Figure 3 for Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds
Figure 4 for Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds
* ACL 2018 
 * published at ACL 2018 
  Access Paper or Ask Questions

The Concept of Criticality in Reinforcement Learning


Oct 16, 2018
Yitzhak Spielberg, Amos Azaria

Figure 1 for The Concept of Criticality in Reinforcement Learning
Figure 2 for The Concept of Criticality in Reinforcement Learning
Figure 3 for The Concept of Criticality in Reinforcement Learning
Figure 4 for The Concept of Criticality in Reinforcement Learning

  Access Paper or Ask Questions

Goldbach's Function Approximation Using Deep Learning


Mar 25, 2018
Avigail Stekel, Merav Chkroun, Amos Azaria

Figure 1 for Goldbach's Function Approximation Using Deep Learning
Figure 2 for Goldbach's Function Approximation Using Deep Learning
Figure 3 for Goldbach's Function Approximation Using Deep Learning
Figure 4 for Goldbach's Function Approximation Using Deep Learning

  Access Paper or Ask Questions

"Is there anything else I can help you with?": Challenges in Deploying an On-Demand Crowd-Powered Conversational Agent


Aug 10, 2017
Ting-Hao Kenneth Huang, Walter S. Lasecki, Amos Azaria, Jeffrey P. Bigham

Figure 1 for "Is there anything else I can help you with?": Challenges in Deploying an On-Demand Crowd-Powered Conversational Agent
Figure 2 for "Is there anything else I can help you with?": Challenges in Deploying an On-Demand Crowd-Powered Conversational Agent
Figure 3 for "Is there anything else I can help you with?": Challenges in Deploying an On-Demand Crowd-Powered Conversational Agent
Figure 4 for "Is there anything else I can help you with?": Challenges in Deploying an On-Demand Crowd-Powered Conversational Agent
* 10 pages. In Proceedings of Conference on Human Computation & Crowdsourcing (HCOMP 2016), 2016, Austin, TX, USA 
  Access Paper or Ask Questions

The DARPA Twitter Bot Challenge


Apr 21, 2016
V. S. Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer, Andrew Stevens, Alexander Dekhtyar, Shuyang Gao, Tad Hogg, Farshad Kooti, Yan Liu, Onur Varol, Prashant Shiralkar, Vinod Vydiswaran, Qiaozhu Mei, Tim Hwang

Figure 1 for The DARPA Twitter Bot Challenge
Figure 2 for The DARPA Twitter Bot Challenge
Figure 3 for The DARPA Twitter Bot Challenge
Figure 4 for The DARPA Twitter Bot Challenge
* Computer 49 (6), 38-46. IEEE, 2016 
 * IEEE Computer Magazine, in press 
  Access Paper or Ask Questions