ICML

Self-Bounded Prediction Suffix Tree via Approximate String Matching

Dongwoo Kim, Christian Walder

Comments Proceedings of the 35th International Conference on Machine Learning

Differentiable Compositional Kernel Learning for Gaussian Processes

Shengyang Sun, Guodong Zhang, Chaoqi Wang, Wenyuan Zeng, Jiaman Li, Roger Grosse

Comments ICML 2018; update proof

Fast Bayesian Intensity Estimation for the Permanental Process

Christian J. Walder, Adrian N. Bishop

Journal ref In Proceedings of the 34th International Conference on Machine Learning, pages: 3579-3588, 6-11 August 2017

Efficient Purely Convolutional Text Encoding

Szymon Malik, Adrian Lancucki, Jan Chorowski

Comments As accepted to: LaCATODA Workshop, ICML 2018

Batched High-dimensional Bayesian Optimization via Structural Kernel Learning

Zi Wang, Chengtao Li, Stefanie Jegelka, Pushmeet Kohli

Comments Proceedings of the 34th International Conference on Machine Learning, Sydney, Australia, PMLR 70, 2017

Max-value Entropy Search for Efficient Bayesian Optimization

Zi Wang, Stefanie Jegelka

Comments Proceedings of the 34th International Conference on Machine Learning, Sydney, Australia, PMLR 70, 2017

Towards fully automated protein structure elucidation with NMR spectroscopy

Piotr Klukowski, Adam Gonczarek

Journal ref 3rd International Workshop on Biomedical Informatics with Optimization and Machine Learning. ICML 2018

Semantic Segmentation with Scarce Data

Isay Katsman, Rohun Tripathi, Andreas Veit, Serge Belongie

Comments ICML 2018 Workshop, camera-ready version

Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam

Mohammad Emtiyaz Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, Akash Srivastava

Comments Camera ready version

Journal ref Thirty-fifth International Conference on Machine Learning, 2018

Budgeted Experiment Design for Causal Structure Learning

AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim

Journal ref 35th International Conference on Machine Learning (ICML), PMLR 80:1719-1728, 2018

MaxMin Linear Initialization for Fuzzy C-Means

Aybükë Oztürk, Stéphane Lallich, Jérôme Darmont, Sylvie Yona Waksman

Journal ref IBaI. 14th International Conference on Machine Learning and Data Mining (MLDM 2018), Jul 2018, New York, United States. Springer, Lecture Notes in Artificial Intelligence, 10934-10935, 2018, Machine Learning and Data Mining in Pattern Recognition. http://www.mldm.de

Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)

Trefor W. Evans, Prasanth B. Nair

Comments Appears in the proceedings of the International Conference on Machine Learning (ICML), 2018

ADMM and Accelerated ADMM as Continuous Dynamical Systems

Guilherme França, Daniel P. Robinson, René Vidal

Journal ref ICML 2018 - Proceedings of the 35th International Conference on Machine Learning

Continuous-Time Flows for Efficient Inference and Density Estimation

Changyou Chen, Chunyuan Li, Liqun Chen, Wenlin Wang, Yunchen Pu, Lawrence Carin

Comments ICML 2018 (fixed a reference)

Modeling Sparse Deviations for Compressed Sensing using Generative Models

Manik Dhar, Aditya Grover, Stefano Ermon

Comments ICML 2018

Learning Policy Representations in Multiagent Systems

Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yura Burda, Harrison Edwards

Comments ICML 2018

Adaptive Three Operator Splitting

Fabian Pedregosa, Gauthier Gidel

Journal ref Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4082-4091, 2018

Scale equivariance in CNNs with vector fields

Diego Marcos, Benjamin Kellenberger, Sylvain Lobry, Devis Tuia

Comments ICML/FAIM 2018 workshop on Towards learning with limited labels: Equivariance, Invariance, and Beyond (oral presentation)

Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors

Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez

Comments ICML 2018. v2 -- Minor edits and fixes typos. arXiv admin note: text overlap with arXiv:1705.10388

Dimensionality-Driven Learning with Noisy Labels

Xingjun Ma, Yisen Wang, Michael E. Houle, Shuo Zhou, Sarah M. Erfani, Shu-Tao Xia, Sudanthi Wijewickrema, James Bailey

Comments In Proceedings of the International Conference on Machine Learning (ICML), 2018

On Acceleration with Noise-Corrupted Gradients

Michael B. Cohen, Jelena Diakonikolas, Lorenzo Orecchia

Comments Appeared in Proc. ICML'18; v2 corrects the statement of Corollary 3.9; v3 added references to concurrent work

Differentiable plasticity: training plastic neural networks with backpropagation

Thomas Miconi, Jeff Clune, Kenneth O. Stanley

Comments Presented at ICML 2018

Journal ref Proceedings of the 35th International Conference on Machine Learning (ICML2018), Stockholm, Sweden, PMLR 80, 2018

Which Training Methods for GANs do actually Converge?

Lars Mescheder, Andreas Geiger, Sebastian Nowozin

Comments conference

Journal ref International Conference on Machine Learning 2018

Beyond the One Step Greedy Approach in Reinforcement Learning

Yonathan Efroni, Gal Dalal, Bruno Scherrer, Shie Mannor

Comments ICML 2018

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

Anish Athalye, Nicholas Carlini, David Wagner

Comments ICML 2018. Source code at https://github.com/anishathalye/obfuscated-gradients

Bayesian Quadrature for Multiple Related Integrals

Xiaoyue Xi, François-Xavier Briol, Mark Girolami

Comments Proceedings of the 35th International Conference on Machine Learning (ICML), PMLR 80:5369-5378, 2018

Improving Transferability of Deep Neural Networks

Parijat Dube, Bishwaranjan Bhattacharjee, Elisabeth Petit-Bois, Matthew Hill

Comments 15 pages, 11 figures, 2 tables, Workshop on Domain Adaptation for Visual Understanding (Joint IJCAI/ECAI/AAMAS/ICML 2018 Workshop) Keywords: deep learning, transfer learning, finetuning, deep neural network, experimental

Learning Dynamics of Linear Denoising Autoencoders

Arnu Pretorius, Steve Kroon, Herman Kamper

Comments 14 pages, 7 figures, accepted at the 35th International Conference on Machine Learning (ICML) 2018

Semi-Supervised Learning via Compact Latent Space Clustering

Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori

Comments Presented as a long oral in ICML 2018. Post-conference camera ready

DCFNet: Deep Neural Network with Decomposed Convolutional Filters

Qiang Qiu, Xiuyuan Cheng, Robert Calderbank, Guillermo Sapiro

Comments Published at ICML 2018