ICMLW 2020

111 papers

A Brief Look at Generalization in Visual Meta-Reinforcement Learning Safa Alver, Doina Precup

A Penalized Likelihood Approach for Statistical Inference in a High-Dimensional Linear Model with Missing Data Jiwei Zhao

A Policy Gradient Method for Task-Agnostic Exploration Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli

A Random Matrix Analysis of Learning with Α-Dropout Mohamed El Amine Seddik, Romain Couillet, Mohamed Tamaazousti

A Study on Intentional-Value-Substitution Training for Regression with Incomplete Information Takuya Fukushima, Tomoharu Nakashima, Taku Hasegawa, Vicenç Torra

Active Online Domain Adaptation Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang

Adversarial Representation Learning for Private Speech Generation David Ericsson, Adam Östberg, Edvin Listo Zec, John Martinsson, Olof Mogren

An Overview of Natural Language State Representation for Reinforcement Learning Brielen Madureira, David Schlangen

Analysis of Predictive Coding Models for Phonemic Representation Learning in Small Datasets María Andrea Cruz Blandón, Okko Räsänen

Attention Option-Critic Raviteja Chunduru, Doina Precup

Beyond the Nav-Graph: Vision-and-Language Navigation in Continuous Environments – Extended Abstract Jacob Krantz, Erik Wijmans, Arjun Majumdar, Dhruv Batra, Stefan Lee

Bootstrapping Unsupervised Deep Music Separation from Primitive Auditory Grouping Principles Prem Seetharaman, Gordon Wichern, Jonathan Le Roux, Bryan Pardo

Bridging Worlds in Reinforcement Learning with Model-Advantage Nirbhay Modhe, Harish K Kamath, Dhruv Batra, Ashwin Kalyan

Causal Discovery in the Presence of Missing Values for Neuropathic Pain Diagnosis Ruibo Tu, Kun Zhang, Bo Christer Bertilson, Clark Glymour, Hedvig Kjellström, Cheng Zhang

Chaotic Continual Learning Touraj Laleh, Mojtaba Faramarzi, Irina Rish, Sarath Chandar

Clustering Data with Nonignorable Missingness Using Semi-Parametric Mixture Models Marie Du Roy de Chaumaray, Matthieu Marbac

COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations Xavier Favory, Konstantinos Drossos, Tuomas Virtanen, Xavier Serra

Combining Variational Continual Learning with FiLM Layers Noel Loo, Siddharth Swaroop, Richard E Turner

Conditioning on "and Nothing Else": Simple Models of Missing Data Between Naive Bayes and Logistic Regression David Poole, Ali Mohammad Mehr, Wan Shing Martin Wang

Continual Deep Learning by Functional Regularisation of Memorable past Pingbo Pan, Siddharth Swaroop, Alexander Immer, Runa Eschenhagen, Richard Turner, Mohammad Emtiyaz Khan

Continual Learning from the Perspective of Compression Xu He, Min Lin

Continual Learning of Object Instances Kishan Parshotam, Mert Kilickaya

Covariate Distribution Aware Meta-Learning Amrith Setlur, Saket Dingliwal, Barnabas Poczos

CPR: Classifier-Projection Regularization for Continual Learning Sungmin Cha, Hsiang Hsu, Flavio du Pin Calmon, and Taesup Moon

Curriculum Learning with Diversity for Supervised Computer Vision Tasks Petru Soviany

Deep Reinforcement Learning Amidst Lifelong Non-Stationarity Annie Xie, James Harrison, Chelsea Finn

Does Imputation Matter? Benchmark for Real-Life Classification Problems. Katarzyna Woźnica, Przemyslaw Biecek

Effective Diversity in Population Based Reinforcement Learning Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts

Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman

ELSIM: End-to-End Learning of Reusable Skills Through Intrinsic Motivation Arthur Aubret, Laetitia Matignon, Salima Hassas

Emergence of Compositional Language in Communication Through Noisy Channel Łukasz Kuciński, Paweł Kołodziej, Piotr Miłoś

Emergence of Multilingualism in Population Based Referential Games Shresth Verma

End-to-End ASR: From Supervised to Semi-Supervised Learning with Modern Architectures Gabriel Synnaeve, Qiantong Xu, Jacob Kahn, Tatiana Likhomanenko, Edouard Grave, Vineel Pratap, Anuroop Sriram, Vitaliy Liptchinsky, Ronan Collobert

Estimating Conditional Density of Missing Values Using Deep Gaussian Mixture Model Marcin Przewięźlikowski, Marek Śmieja, Łukasz Struski

Evaluating Logical Generalization in Graph Neural Networks Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton

Exchangeable Models in Meta Reinforcement Learning Iryna Korshunova, Jonas Degrave, Joni Dambre, Arthur Gretton, Ferenc Huszar

Explore Then Execute: Adapting Without Rewards via Factorized Meta-Reinforcement Learning Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn

Extended Abstract: Improving Vision-and-Language Navigation with Image-Text Pairs from the Web Arjun Majumdar, Ayush Shrivastava, Stefan Lee, Peter Anderson, Devi Parikh, Dhruv Batra

Federated Continual Learning with Weighted Inter-Client Transfer Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, Sung Ju Hwang

Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent Mehdi Abbana Bennani, Masashi Sugiyama

Generalizing Curricula for Reinforcement Learning Sanmit Narvekar, Peter Stone

Gradient Based Memory Editing for Task-Free Continual Learning Xisen Jin, Junyi Du, Xiang Ren

Handling Missing Data in Decision Trees: A Probabilistic Approach Pasha Khosravi, Antonio Vergari, YooJung Choi, Yitao Liang, Guy Van den Broeck

Hierarchical Expert Networks for Meta-Learning Heinke Hihn, Daniel A. Braun

Hierarchical Reinforcement Learning for Efficent Exploration and Transfer Lorenzo Steccanella, Simone Totaro, Damien Allonsius, Anders Jonsson

How to Deal with Missing Data in Supervised Deep Learning? Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen

How to Miss Data? Reinforcement Learning for Environments with High Observation Cost Mehmet Koseoglu, Ayca Ozcelikkale

Importance Weighting with a Adversarial Network for Large-Scale Sleep Staging Samaneh Nasiri, Gari D. Clifford

Imputation of Missing Behavioral Measures in Connectome-Based Predictive Modelling Qinghao Liang, Dustin Scheinost

Inferring Causal Dependencies Between Chaotic Dynamical Systems from Sporadic Time Series Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau

Information Theoretic Approaches for Testing Missingness in Predictive Models Shreyas A Bhave, Rajesh Ranganath, Adler Perotte

Investigating Self-Supervised Pre-Training for End-to-End Speech Translation Ha Nguyen, Fethi Bougares, Natalia Tomashenko, Yannick Estève, Laurent Besacier

La-MAML: Look-Ahead Meta Learning for Continual Learning Gunshi Gupta, Karmesh Yadav, Liam Paull

Language Agnostic Speech Embeddings for Emotion Classification Apoorv Nandan, Jithendra Vepa

Language-Conditioned Goal Generation: A New Approach to Language Grounding in RL Cédric Colas, Ahmed Akakzia, Pierre-Yves Oudeyer, Mohamed Chetouani, Olivier Sigaud

Language-Goal Imagination to Foster Creative Exploration in Deep RL Tristan Karch, Nicolas Lair, Cédric Colas, Jean-Michel Dussoux, Clément Moulin-Frier, Peter Ford Dominey, Pierre-Yves Oudeyer

Learning Intrinsically Motivated Options to Stimulate Policy Exploration Louis Bagot, Kevin Mets, Steven Latré

Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision Abhinav Shukla, Stavros Petridis, Maja Pantic

Lifelong Learning of Factored Policies via Policy Gradients Jorge A Mendez, Eric Eaton

Lifelong Learning Using Eigentasks: Task Separation, Skill Acquisition and Selective Transfer Aswin Raghavan, Jesse Hostetler, Indranil Sur, Abrar Rahman, Ajay Divakaran

Logical Composition in Lifelong Reinforcement Learning Geraud Nangue Tasse, Steven James, Benjamin Rosman

Lung Segmentation from Chest X-Rays Using Variational Data Imputation Raghavendra Selvan, Erik Dam, Nicki Skafte Detlefsen, Sofus Rischel, Kaining Sheng, Mads Nielsen, Akshay Pai

MemeSem:A Multi-Modal Framework for Sentimental Analysis of Meme via Transfer Learning Raj Ratn Pranesh, Ambesh Shekhar

Meta-Learning for Recalibration of EMG-Based Upper Limb Prostheses Krsto Proroković, Michael Wand, Jürgen Schmidhuber

Meta-Learning GNN Initializations for Low-Resource Molecular Property Prediction Cuong Q. Nguyen, Constantine Kreatsoulas, Kim M. Branson

Missing Rating Imputation Based on Product Reviews via Deep Latent Variable Models Dingge Liang, Marco Corneli, Pierre Latouche, Charles Bouveyron

Missing the Point: Non-Convergence in Iterative Imputation Algorithms Hanne I. Oberman, Stef van Buuren, Gerko Vink

Multi-Label Learning with Missing Values Using Combined Facial Action Unit Datasets Jaspar Pahl, Ines Rieger, Dominik Seuss

Multi-Output Prediction of Global Vegetation Distribution with Incomplete Data Rita Beigaite, Jesse Read, Indre Zliobaite

Multi-Time Attention Networks for Irregularly Sampled Time Series Satya Narayan Shukla, Benjamin Marlin

Multilayer Neuromodulated Architectures for Memory-Constrained Online Continual Learning Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash

Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine

Off-Policy Adversarial Inverse Reinforcement Learning Samin Yeasar Arnob

Off-Policy Meta-Reinforcement Learning Based on Feature Embedding Spaces Takahisa Imagawa, Takuya Hiraoka, Yoshimasa Tsuruoka

On the Relationship Between Structure in Natural Language and Models of Sequential Decision Processes Roma Patel, Rafael Rodriguez-Sanchez, George Konidaris

Online Mixed Missing Value Imputation Using Gaussian Copula Eric Landgrebe, Yuxuan Zhao, Madeleine Udell

Optimal Recovery of Missing Values for Non-Negative Matrix Factorization: A Probabilistic Error Bound Rebecca Chen, Lav R. Varshney

Optimizing for the Future in Non-Stationary MDPs Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas

OtoWorld: Towards Learning to Separate by Learning to Move Omkar Ranadive, Grant Gasser, David Terpay, Prem Seetharaman

PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees Jonas Rothfuss, Vincent Fortuin, Andreas Krause

Path Imputation Strategies for Signature Models Michael Moor, Max Horn, Christian Bock, Karsten Borgwardt, Bastian Rieck

PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards Prasoon Goyal, Scott Niekum, Ray Mooney

Pow-Wow: A Dataset and Study on Collaborative Communication in Pommerman Takuma Yoneda, Matthew Walter, Jason Naradowsky

Pre-Trained Word Embeddings for Goal-Conditional Transfer Learning in Reinforcement Learning Matthias Hutsebaut-Buysse, Kevin Mets, Steven Latré

Predicting Feature Imputability in the Absence of Ground Truth Niamh McCombe, Xuemei Ding, Girijesh Prasad, David P Finn, Stephen Todd, Paula L McClean, Kongfatt Wong-Lin

Processing of Incomplete Images by (graph) Convolutional Neural Networks Tomasz Danel, Marek Śmieja, Łukasz Struski, Przemysław Spurek, Lukasz Maziarka

Pseudo-Rehearsal for Continual Learning with Normalizing Flows Jary Pomponi, Simone Scardapane, Aurelio Uncini

RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning Riccardo Del Chiaro, Bartłomiej Twardowski, Andrew D. Bagdanov, Joost Van De Weijer

Reinforcement Communication Learning in Different Social Network Structures Marina Dubova, Arsenii Kirillovich Moskvichev, Rob Goldstone

Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov

Self-Supervised Pitch Detection by Inverse Audio Synthesis Jesse Engel, Rigel Swavely, Lamtharn Hanoi Hantrakul, Adam Roberts, Curtis Hawthorne

Sharing Less Is More: Lifelong Learning in Deep Networks with Selective Layer Transfer Seungwon Lee, Sima Behpour, Eric Eaton

Skill Discovery for Exploration and Planning Using Deep Skill Graphs Akhil Bagaria, Jason Crowley, Jing Wei Nicholas Lim, George Konidaris

Storing Encoded Episodes as Concepts for Continual Learning Ali Ayub, Alan R. Wagner

Tackling Non-Forgetting and Forward Transfer with a Unified Lifelong Learning Approach Xinyu Yun, Tanner A Bohn, Charles X. Ling

Taming the Herd: Multi-Modal Meta-Learning with a Population of Agents Robert Müller, Jack Parker-Holder, Aldo Pacchiano

Task Agnostic Continual Learning via Meta Learning Xu He, Jakub Sygnowski, Alexandre Galashov, Andrei Alex Rusu, Yee Whye Teh, Razvan Pascanu

The Dynamic Latent Block Model for Sparse and Evolving Count Matrices Giulia Marchello, Marco Corneli, Charles Bouveyron

The Impact of Incomplete Data on Quantile Regression for Longitudinal Data Anneleen Verhasselt, Alvaro José Flórez, Ingrid Van Keilegom, Geert Molenberghs

Towards an Unsupervised Method for Model Selection in Few-Shot Learning Simon Guiroy, Vikas Verma, Christopher Pal

Understanding Self-Attention of Self-Supervised Audio Transformers Shu-wen Yang, Andy T. Liu, Hung-yi Lee

Unsupervised Progressive Learning and the STAM Architecture James Smith, Seth Baer, Cameron Taylor, Constantine

Unsupervised Speech Separation Using Mixtures of Mixtures Scott Wisdom, Efthymios Tzinis, Hakan Erdogan, Ron J Weiss, Kevin Wilson, John R. Hershey

Using Self-Supervised Learning of Birdsong for Downstream Industrial Audio Classification Patty Ryan, Sean Takafuji, Chenhao Yang, Nile Wilson, Christopher McBride

VAEM: A Deep Generative Model for Heterogeneous Mixed Type Data Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang

VAEs in the Presence of Missing Data Mark Collier, Alfredo Nazabal, Chris Williams

Variance Estimation After Kernel Ridge Regression Imputation Hengfang Wang, Jae Kwang Kim

Visna---Visualising Multivariate Missing Values Antony Unwin, Alexander Pilhoefer

Wandering Within a World: Online Contextualized Few-Shot Learning Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer, Richard S. Zemel

WordCraft: An Environment for Benchmarking Commonsense Agents Minqi Jiang, Jelena Luketina, Nantas Nardelli, Pasquale Minervini, Philip Torr, Shimon Whiteson, Tim Rocktäschel

Working with Deep Generative Models and Tabular Data Imputation Ramiro Camino, Christian Hammerschmidt, Radu State