Huihan Yao, Ying Chen, Qinyuan Ye and

Xisen Jin, Xiang Ren

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machine learning, fairness, language

Tianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi Jaakkola

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Deep Learning - Generative Models and Autoencoders

Lingkai Kong, Haoming Jiang, Yuchen Zhuang and

Jie Lyu, Tuo Zhao, Chao Zhang

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augmented training, in-distribution calibration, text classification, expectation error

Akhil Kedia, Sai Chetan Chinthakindi

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Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin

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machine learning, federated learning

Wenhu Chen, Jianshu Chen, Yu Su and

Zhiyu Chen, William Yang Wang

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Logical Generation, neural NLG, surface-level realizations, logical inference

Guy Emerson

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Amortised Inference, inference, semantic composition, Autoencoding

Esther Rolf, Michael Jordan, Benjamin Recht

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Yanru Qu, Dinghan Shen, Yelong Shen and

Sandra Sajeev, Weizhu Chen, Jiawei Han

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consistency training, contrastive learning, data augmentation, natural language understanding

Alexander Lew, Monica Agrawal, David Sontag, Vikash Mansinghka

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Thong Nguyen, Anh Tuan Luu

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optimization, contrastive learning

Koar Marntirosian, Tom Schrijvers, Bruno C. d. S. Oliveira, Georgios Karachalias

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coherence, resolution, modus ponens, family polymorphism, nested composition, intersection types

Jiani Huang, Ziyang Li, Binghong Chen and

Karan Samel, Mayur Naik, Le Song, Xujie Si

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deep learning, transformers, vision

Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi

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Probabilistic Methods

Vaibhav Kumar, Alan W Black

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Clarification Generation, Question answering, classifying questions, downstream question-answering

Lanqing Li, Rui Yang, Dijun Luo

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distance metric learning, offline/batch reinforcement learning, meta-reinforcement learning, contrastive learning, multi-task reinforcement learning

Charles Dickens, Connor Pryor, Eriq Augustine and

Alexander Miller, Lise Getoor

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Probabilistic Methods, Graphical Models

Nikunj Saunshi, Sadhika Malladi, Sanjeev Arora

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representation learning, self-supervised learning, language models, theory, transfer learning, natural language processing, unsupervised learning

Zhisong Zhang, Xiang Kong, Zhengzhong Liu and

Xuezhe Ma, Eduard Hovy

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Implicit Detection, implicit task, modeling, argument detection

Luyang Huang, Lingfei Wu, Lu Wang

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Knowledge Summarization, abstractive summarization, semantic interpretation, generation summaries

Junwen Bai, Weiran Wang, Yingbo Zhou, Caiming Xiong

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Unsupervised Learning, Mutual Information, Masked Reconstruction, Sequence Data

Manuel Bodirsky, Wied Pakusa, and Jakub Rydval

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fixed-point logic, Maltsev conditions, temporal constraint satisfaction problems

Jianxing Yu, Wei Liu, Shuang Qiu and

Qinliang Su, Kai Wang, Xiaojun Quan, Jian Yin

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Low-Resource Questions, generating questions, machine comprehension, multi-hop model

Elbruz Ozen, Alex Orailoglu

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deep learning, information redundancy, pruning

Maria Gorinova, Dave Moore, Matthew Hoffman

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Probabilistic Inference - Models and Probabilistic Programming

Fan Yan, Ming Li

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Multidisciplinary Topics and Applications, Knowledge-based Software Engineering, Mining Codebase and Software Repository

Sanjoy Dasgupta, Sivan Sabato

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Xiaojing Yu, Anxiao Jiang

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Sergul Aydore, William Brown, Michael Kearns and

Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit Siva

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Optimization, Stochastic Optimization, Optimization, Convex Optimization; Probabilistic Methods; Theory; Theory, Control Theory, Social Aspects of Machine Learning, Privacy, Anonymity, and Security

Zhuo Wang, Wei Zhang, Ning Liu, Jianyong Wang

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optimization, machine learning, representation learning, interpretability

Yiwei Wang, Yujun Cai, Yuxuan Liang and

Henghui Ding, Changhu Wang, Siddharth Bhatia, Bryan Hooi

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deep learning, machine learning, graph learning

Siddhant Garg, Yingyu Liang

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Guangyi Zhang, Aristides Gionis

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sampling, classifier, pattern mining, rule learning, diversification, rule sets

Alvin Wan, Lisa Dunlap, Daniel Ho and

Jihan Yin, Scott Lee, Suzanne Petryk, Sarah A Bargal, Joseph E Gonzalez

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computer vision, explainability, interpretability

Haoyu Wang, Muhao Chen, Hongming Zhang, Dan Roth

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understanding language, temporal extraction, event construction, inducing complexes

Matt Chapman-Rounds, Umang Bhatt, Erik Pazos and

Marc-Andre Schulz, Konstantinos Georgatzis

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Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto and

Luigi Gresele, Bernhard Schoelkopf

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invariances, gradient alignment, consistency

Manuel Rigger, Zhendong Su

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database testing, three-valued logic, DBMS testing, test oracle

Alexander K. Lew, Marco Cusumano-Towner, Benjamin Sherman and

Michael Carbin, Vikash Mansinghka

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Probabilistic programming, programmable inference, type systems

Xiaomei Zhang, Yingying Chen, Bingke Zhu and

Jinqiao Wang, Ming Tang

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human parsing, segmentation, part-aware context network, part class module, relational aggregation module, relational dispersion module