Timezone: »
Author Information
Ambrish Rawat (IBM Research)
Armand Joulin (Facebook AI research)
Peter A Jansen (University of Arizona)
Interdisciplinary cognitive artificial intelligence researcher working in natural language processing, studying how to create robust methods of inference for question answering that integrate multiple pieces of knowledge to arrive at answers, and are able to explain their reasoning.
Jay Yoon Lee (Carnegie Mellon University)
Muhao Chen (UCLA)
Frank F. Xu (Shanghai Jiao Tong University)
Patrick Verga (University of Massachusetts, Amherst)
Brendan Juba (Washington University in St. Louis)
Anca Dumitrache (Vrije Universiteit Amsterdam)
I am a PhD student in the [Web & Media](https://wm.cs.vu.nl/) group at [Vrije Universiteit Amsterdam](http://few.vu.nl/). For the past 4 years I've been involved in the [CrowdTruth](http://crowdtruth.org/) project, where we look into how to capture and interpret inter-annotator disagreement in *crowdsourcing*. I am investigating how to use this disagreement to get better training data for *natural language processing* models. My supervisors are Prof. [Lora Aroyo](https://loraaroyo.wordpress.com/) and Dr. [Chris Welty](https://research.google.com/pubs/104789.html). Other interests I have include *machine learning*, *Semantic Web*, *open data* and *data science* in general. My programming languages of choice are *R* and *Python* (particularly the scientific Python stack). In the past, I've done internships in the Watson group at [IBM Research](http://research.ibm.com/), and in the NLP department at [Google Research](https://research.google.com/), both in New York. I've also been a recipient of the [IBM PhD Fellowship](http://www.research.ibm.com/university/awards/phdfellowship.shtml) from 2014 to 2016.
Sharmistha Jat (Indian Institute of Science)
Robert Logan (UC Irvine)
Dhanya Sridhar (University of California Santa Cruz)
Fan Yang (Carnegie Mellon University)
Rajarshi Das (University of Massachusetts, Amherst)
Pouya Pezeshkpour (University of California, Irvine)
Nicholas Monath (University of Massachusetts Amherst)
More from the Same Authors
-
2021 : Cutting Down on Prompts and Parameters:Simple Few-Shot Learning with Language Models »
Robert Logan · Ivana Balazevic · Eric Wallace · Fabio Petroni · Sameer Singh · Sebastian Riedel -
2021 : Certified Federated Adversarial Training »
Giulio Zizzo · Ambrish Rawat -
2022 : Quantifying Social Biases Using Templates is Unreliable »
Preethi Seshadri · Pouya Pezeshkpour · Sameer Singh -
2022 Poster: Structured Energy Network As a Loss »
Jay Yoon Lee · Dhruvesh Patel · Purujit Goyal · Wenlong Zhao · Zhiyang Xu · Andrew McCallum -
2021 : Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions »
Siddartha Devic · Zihao Deng · Brendan Juba -
2021 : Cutting Down on Prompts and Parameters:Simple Few-Shot Learning with Language Models »
Robert Logan · Ivana Balazevic · Eric Wallace · Fabio Petroni · Sameer Singh · Sebastian Riedel -
2021 Poster: Capacity and Bias of Learned Geometric Embeddings for Directed Graphs »
Michael Boratko · Dongxu Zhang · Nicholas Monath · Luke Vilnis · Kenneth L Clarkson · Andrew McCallum -
2021 Poster: XCiT: Cross-Covariance Image Transformers »
Alaaeldin Ali · Hugo Touvron · Mathilde Caron · Piotr Bojanowski · Matthijs Douze · Armand Joulin · Ivan Laptev · Natalia Neverova · Gabriel Synnaeve · Jakob Verbeek · Herve Jegou -
2020 Poster: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments »
Mathilde Caron · Ishan Misra · Julien Mairal · Priya Goyal · Piotr Bojanowski · Armand Joulin -
2019 : Opening Remarks »
Manzil Zaheer · Nicholas Monath · Ari Kobren · Junier Oliva · Barnabas Poczos · Ruslan Salakhutdinov · Andrew McCallum -
2019 Workshop: Sets and Partitions »
Nicholas Monath · Manzil Zaheer · Andrew McCallum · Ari Kobren · Junier Oliva · Barnabas Poczos · Ruslan Salakhutdinov -
2019 : Poster Spotlights A (23 posters) »
DongHa Bahn · Xiaoran Xu · Shih-Chieh Su · Daniel Cunnington · Wonseok Hwang · Sarthak Dash · Alberto Camacho · Theodoros Salonidis · Shiyang Li · Yuyu Zhang · Habibeh Naderi · Zhe Zeng · Pasha Khosravi · Pedro Colon-Hernandez · Dimitris Diochnos · David Windridge · Robin Manhaeve · Vaishak Belle · Brendan Juba · Naveen Sundar Govindarajulu · Joe Bockhorst -
2019 Poster: Implicitly learning to reason in first-order logic »
Vaishak Belle · Brendan Juba -
2019 Poster: Game Design for Eliciting Distinguishable Behavior »
Fan Yang · Liu Leqi · Yifan Wu · Zachary Lipton · Pradeep Ravikumar · Tom M Mitchell · William Cohen -
2018 Poster: Compact Representation of Uncertainty in Clustering »
Craig Greenberg · Nicholas Monath · Ari Kobren · Patrick Flaherty · Andrew McGregor · Andrew McCallum -
2017 : POSTER: Learning to organize knowledge with N-gram machines »
Fan Yang -
2017 : Differentiable Learning of Logical Rules for Knowledge Base Reasoning »
William Cohen · Fan Yang -
2017 Poster: Good Semi-supervised Learning That Requires a Bad GAN »
Zihang Dai · Zhilin Yang · Fan Yang · William Cohen · Ruslan Salakhutdinov -
2017 Poster: Differentiable Learning of Logical Rules for Knowledge Base Reasoning »
Fan Yang · Zhilin Yang · William Cohen -
2017 Poster: Unbounded cache model for online language modeling with open vocabulary »
Edouard Grave · Moustapha Cisse · Armand Joulin -
2016 Workshop: Machine Intelligence @ NIPS »
Tomas Mikolov · Baroni Marco · Armand Joulin · Germán Kruszewski · Angeliki Lazaridou · Klemen Simonic -
2015 Poster: Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets »
Armand Joulin · Tomas Mikolov -
2015 Spotlight: Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets »
Armand Joulin · Tomas Mikolov