Jheng-Hong Yang, Sheng-Chieh Lin, Rodrigo Nogueira and

Ming-Feng Tsai, Chuan-Ju Wang, Jimmy Lin

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Doruk Kilitcioglu, Serdar Kadioglu

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Alexander Miserlis Hoyle, Pranav Goel, Philip Resnik

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topic models, knowledge distillation, probabilistic models, pretrained transformers

Saurabh Srivastava, Mayur Patidar, Sudip Chowdhury and

Puneet Agarwal, Indrajit Bhattacharya, Gautam Shroff

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Jie Gu, Feng Wang, Qinghui Sun and

Zhiquan Ye, Xiaoxiao Xu, Jingmin Chen, Jun Zhang

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Xiaohan Chen, Zhangyang Wang, Siyu Tang, Krikamol Muandet

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Ting-Hsiang Wang, Xia Hu, Haifeng Jin and

Qingquan Song, Xiaotian Han, Zirui Liu

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Recommender Systems, Hyperparameter Tuning, Neural Architecture Search, Automated Machine Learning, Model Search

Yu Zhang, Gongbo Liang, Nathan Jacobs

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domain adaptation, semi-supervised learning, image classification, memory bank, feature alignment

Yunyi Zhang, Jiaming Shen, Jingbo Shang, Jiawei Han

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Empower Expansion, Entity expansion, NLP applications, question answering

Tanmay Shankar, Shubham Tulsiani, Lerrel Pinto, Abhinav Gupta

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Learning from Demonstration, Imitation Learning, Motor Primitives

Eric Wang, Pasha Khosravi, Guy Van den Broeck

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Machine Learning, Explainable/Interpretable Machine Learning, Explainability, Exact Probabilistic Inference

Ruoxi Sun, Hanjun Dai, Li Li and

Steven Kearnes, Bo Dai

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deep learning, machine learning, graph learning

Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb, Ameet Talwalkar

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Interpretability, Generalization, Local Explanations, Learning Theory

Xiantong Zhen, Yingjun Du, Huan Xiong and

Qiang Qiu, Cees Snoek, Ling Shao

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Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss

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Supervised Learning

Youngwoon Lee, Andrew Szot, Shao-Hua Sun, Joseph Lim

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reinforcement learning and planning

Martin Avanzini, Georg Moser, Michael Schaper

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probabilistic programs, automation, average complexity, modularity

Ian Osband, Yotam Doron, Matteo Hessel and

John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvari, Satinder Singh, Benjamin Van Roy, Richard Sutton, David Silver, Hado Van Hasselt

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reinforcement learning, benchmark, core issues, scalability, reproducibility

Yishay Mansour, Mehryar Mohri, Jae Ro and

Ananda Theertha Suresh, Ke Wu

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Fan Xie, Alexander Chowdhury, Clara De Paolis Kaluza and

Linfeng Zhao, Lawson Wong, Rose Yu

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Lars C. Gleim, Rafael Schimassek, Dominik Hüser and

Maximilian Peters, Christoph Krämer, Michael Cochez et al.

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Serban Stan, Mohammad Rostami

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Dmytro Borysenko, Dmytro Mykheievskyi, Viktor Porokhonskyy

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Kevin Xie, Homanga Bharadhwaj, Danijar Hafner and

Animesh Garg, Florian Shkurti

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Partial Amortization, Model Predictive Control, Planning, Mutual Information, Skill Discovery, World Models, Model-Based Reinforcement Learning

Frank F. Xu, Zhengbao Jiang, Pengcheng Yin and

Bogdan Vasilescu, Graham Neubig

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Open-domain generation, NL-to-code generation, data augmentation, retrieval-based re-sampling

Xiaodong Liu, Yu Wang, Jianshu Ji and

Hao Cheng, Xueyun Zhu, Emmanuel Awa, Pengcheng He, Weizhu Chen, Hoifung Poon, Guihong Cao, Jianfeng Gao

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Natural Understanding, NLU tasks, classification, regression

Carlos Gemmell, Federico Rossetto, Jeffrey Dalton

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code generation, neural machine translation, code retrieval

Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi and

Sho Yokoi, Tatsuki Kuribayashi, Ryuto Konno, Kentaro Inui

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Named Recognition, Interpretable rationales, model predictions, structured prediction

Giovanni Trappolini, Luca Cosmo, Luca Moschella and

Riccardo Marin, Simone Melzi, Emanuele Rodolà

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deep learning, reinforcement learning and planning, transformers

Ruihui Li, Xianzhi Li, Pheng-Ann Heng, Chi-Wing Fu

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auto-augmentation framework, point cloud processing, sample-aware, jointly optimizing, classification

Maxwell Crouse, Constantine Nakos, Ibrahim Abdelaziz, Ken Forbus

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Yoav Wald, Amir Feder, Daniel Greenfeld, Uri Shalit

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machine learning, domain adaptation, causality

Fengyi Shen, Akhil Gurram, Ahmet Faruk Tuna and

Onay Urfalioglu, Alois C. Knoll

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domain adaptation, semantic segmentation, autonomous driving, image-to-image translation, unsupervised learning, domain transfer, scene understanding, urban scene segmentation

Deepanway Ghosal, Devamanyu Hazarika, Abhinaba Roy and

Navonil Majumder, Rada Mihalcea, Soujanya Poria

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Sentiment Analysis, Cross-domain analysis, KinGDOM, Knowledge-Guided Adaptation

Sanyuan Chen, Yutai Hou, Yiming Cui and

Wanxiang Che, Ting Liu, Xiangzhan Yu

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pretraining, pretraining tasks, learning tasks, fine-tuning bert-large

Tassilo Klein, Moin Nabi

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Commonsense Reasoning, Pronoun problems, pronoun disambiguation, commonsense tasks

Chris Reinke, Mayalen Etcheverry, Pierre-Yves Oudeyer

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deep learning, unsupervised Learning, self-organization, game-of-life

Nishtha Madaan, Inkit Padhi, Naveen Panwar, Diptikalyan Saha

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Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, Isabelle Augenstein

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downstream tasks, machine learning, explainability techniques, diverse techniques

Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc

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deep learning, interpretability