Gregory Canal, Matthieu Bloch, Christopher Rozell

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Anjaly Parayil, He Bai, Jemin George, Prudhvi Gurram

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Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba and

Karl Wimmer, Ning Xie

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Alexander Li, Deepak Pathak

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deep learning, optimization, reinforcement learning and planning

Rizal Fathony, Zico Kolter

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Sungjoon Choi, Sanghoon Hong, Kyungjae Lee, Sungbin Lim

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robust learning, bayesian deep learning, semi-supervised learning

Huazheng Wang, Qian Zhao, Qingyun Wu and

Shubham Chopra, Abhinav Khaitan, Hongning Wang

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contextual bandits, Differential privacy, collaborative learning

Junnan Li, Richard Socher, Steven C.H. Hoi

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label noise, semi-supervised learning

Yuzhou Cao, Lei Feng, Yitian Xu and

Bo An, Gang Niu, Masashi Sugiyama

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Algorithms, Semi-Supervised Learning

Jun Sun, Gang Wang, Georgios B. Giannakis and

Qinmin Yang, Zaiyue Yang

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Amirhossein Reisizadeh, Farzan Farnia, Ramtin Pedarsani, Ali Jadbabaie

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Zhilei Wang, Pranjal Awasthi, Christoph Dann and

Ayush Sekhari, Claudio Gentile

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deep learning, active learning

Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang and

Aditya Balu, Ethan Herron, Chinmay Hegde, Soumik Sarkar

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Optimization, Distributed and Parallel Optimization

Eirikur Agustsson, Lucas Theis

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Zixin Wen, Yuanzhi Li

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Theory, Deep learning Theory

Andreas Maurer, Daniela Angela Parletta, Andrea Paudice, Massimiliano Pontil

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Theory, Statistical Learning Theory

Jiahao Ding, Guannan Liang, Jinbo Bi, Miao Pan

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Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig

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Deep Learning, Embedding and Representation learning

Sai Praneeth Reddy Karimireddy, Satyen Kale, Mehryar Mohri and

Sashank Jakkam Reddi, Sebastian Stich, Ananda Theertha Suresh

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Optimization - Convex

Mingyuan Zhang, Jane Lee, Shivani Agarwal

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Algorithms, Supervised Learning

Mingrui Zhang, Lin Chen, Aryan Mokhtari and

Hamed Hassani, Amin Karbasi

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Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis

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PAC learning,

Dipendra Misra, Qinghua Liu, Chi Jin, John Langford

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Factored MDP, State abstraction, Noise-contrastive learning, Rich observation, Reinforcement learning theory

Junxian He, Jiatao Gu, Jiajun Shen, Marc'Aurelio Ranzato

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self-training, semi-supervised learning, neural sequence generatioin

Mark Bun, Marco L Carmosino, Jessica Sorrell

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Privacy, fairness, Excess risk bounds and generalization error bounds, PAC learning

Ben Eysenbach, Russ Salakhutdinov, Sergey Levine

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reinforcement learning and planning, robustness

Jesse Zhang, Haonan Yu, Wei Xu

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reinforcement learning, unsupervised skill discovery, exploration, options, hierarchical reinforcement learning

Ehtsham Elahi, Ashok Chandrashekar

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collaborative filtering, embeddings, hierarchical slates, recommender systems, user models

Salman Habib, Allison Beemer, Joerg Kliewer

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Algorithms -> Similarity and Distance Learning, Applications -> Network Analysis

Filippos Christianos, Georgios Papoudakis, Arrasy Rahman, Stefano V. Albrecht

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Reinforcement Learning and Planning

Asish Ghoshal, Xilun Chen, Sonal Gupta and

Luke Zettlemoyer, Yashar Mehdad

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calibration, semantic parsing, structured prediction, label smoothing

Jenny Hamer, Mehryar Mohri, Ananda Theertha Suresh

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General Machine Learning Techniques

Vivien Cabannes, Loucas Pillaud-Vivien, Francis Bach, Alessandro Rudi

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machine learning, kernel methods, semi-supervised learning

Bingbin Liu, Pradeep Ravikumar, Andrej Risteski

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Ayoub El Hanchi, David Stephens

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Leonard Berrada, M. Pawan Kumar, Andrew Zisserman

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Deep Learning - General

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Transfer, Multitask and Meta-learning

MINGZHI DONG, Xiaochen Yang, Rui Zhu and

Yujiang Wang, Jing-Hao Xue

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Raphaël Dang-Nhu

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theory, optimization