ICML

Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret

Alina Beygelzimer, Francesco Orabona, Chicheng Zhang

Comments 22 pages, 2 figures; ICML 2017; this version includes additional discussions of Newtron, and a variant of SOBA that directly uses an online exp-concave optimization oracle

Stochastic Gradient Monomial Gamma Sampler

Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin

Comments Published on ICML 2017

Journal ref Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3996-4005, 2017

Parametric Exponential Linear Unit for Deep Convolutional Neural Networks

Ludovic Trottier, Philippe Giguère, Brahim Chaib-draa

Comments 16th IEEE International Conference On Machine Learning And Applications, 2017

Learning to Generate Long-term Future via Hierarchical Prediction

Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee

Comments International Conference on Machine Learning (ICML) 2017

Deep Architectures for Automated Seizure Detection in Scalp EEGs

Meysam Golmohammadi, Saeedeh Ziyabari, Vinit Shah, Silvia Lopez de Diego, Iyad Obeid, Joseph Picone

Comments nder review in International Conference on Machine Learning, Stockholm, Sweden

Language Generation with Recurrent Generative Adversarial Networks without Pre-training

Ofir Press, Amir Bar, Ben Bogin, Jonathan Berant, Lior Wolf

Comments Presented at the 1st Workshop on Learning to Generate Natural Language at ICML 2017

Learning Visual Reasoning Without Strong Priors

Ethan Perez, Harm de Vries, Florian Strub, Vincent Dumoulin, Aaron Courville

Comments Full AAAI 2018 paper is at arXiv:1709.07871. Presented at ICML 2017's Machine Learning in Speech and Language Processing Workshop. Code is at http://github.com/ethanjperez/film

Forward and Reverse Gradient-Based Hyperparameter Optimization

Luca Franceschi, Michele Donini, Paolo Frasconi, Massimiliano Pontil

Comments - Posted the ICML Camera Ready version. - Added a link to a newer package implementation of the algorithms

Journal ref Franceschi, L., Donini, M., Frasconi, P. & Pontil, M.. (2017). Forward and Reverse Gradient-Based Hyperparameter Optimization. Proceedings of the 34th International Conference on Machine Learning, in PMLR 70:1165-1173

Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening

Mohsen Ahmadi Fahandar, Eyke Hüllermeier, Inés Couso

Comments Proceedings of the 34th International Conference on Machine Learning (ICML 2017), 10 pages

Journal ref Proceedings of the 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia, PMLR 70:1078-1087, 2017

Transferring Autonomous Driving Knowledge on Simulated and Real Intersections

David Isele, Akansel Cosgun

Comments Appeared in Lifelong Learning Workshop @ ICML 2017. arXiv admin note: text overlap with arXiv:1705.01197

Variants of RMSProp and Adagrad with Logarithmic Regret Bounds

Mahesh Chandra Mukkamala, Matthias Hein

Comments ICML 2017, 16 pages, 23 figures

Knowledge Graph Completion via Complex Tensor Factorization

Théo Trouillon, Christopher R. Dance, Johannes Welbl, Sebastian Riedel, Éric Gaussier, Guillaume Bouchard

Comments 38 pages, accepted in JMLR. This is an extended version of the article "Complex embeddings for simple link prediction" (ICML 2016)

Adversarial Feature Matching for Text Generation

Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin

Comments Accepted by ICML 2017

Iterative Machine Teaching

Weiyang Liu, Bo Dai, Ahmad Humayun, Charlene Tay, Chen Yu, Linda B. Smith, James M. Rehg, Le Song

Comments Published in ICML 2017

Large-Margin Softmax Loss for Convolutional Neural Networks

Weiyang Liu, Yandong Wen, Zhiding Yu, Meng Yang

Comments Published in ICML 2016 (with typo fixed)

Detecting Adversarial Samples from Artifacts

Reuben Feinman, Ryan R. Curtin, Saurabh Shintre, Andrew B. Gardner

Comments Submitted to ICML 2017

Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach

Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang

Comments 33 pages, 4 tables. A preliminary version of this paper titled "Near-Optimal Experimental Design via Regret Minimization" with weaker results appeared in the Proceedings of the 34th International Conference on Machine Learning (ICML 2017), Sydney

Device Placement Optimization with Reinforcement Learning

Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean

Comments To appear at ICML 2017

Bayesian Belief Updating of Spatiotemporal Seizure Dynamics

Gerald K Cooray, Richard Rosch, Torsten Baldeweg, Louis Lemieux, Karl Friston, Biswa Sengupta

Comments ICML 2017 Time Series Workshop

Approximate Bayesian inference as a gauge theory

Biswa Sengupta, Karl Friston

Comments Extended version published in PLoS Biology, ICML 2017 Computational Biology Workshop (spotlight presentation)

Likelihood Estimation for Generative Adversarial Networks

Hamid Eghbal-zadeh, Gerhard Widmer

Comments ICML 2017 Workshop on Implicit Models

Optimal and Adaptive Off-policy Evaluation in Contextual Bandits

Yu-Xiang Wang, Alekh Agarwal, Miroslav Dudik

Journal ref International Conference on Machine Learning (pp. 3589-3597) (2017)

Dictionary Learning for Massive Matrix Factorization

Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux

Journal ref Proceedings of the International Conference on Machine Learning, 2016, pp 1737-1746

Regret Minimization in Behaviorally-Constrained Zero-Sum Games

Gabriele Farina, Christian Kroer, Tuomas Sandholm

Comments Published at ICML 17

Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning

Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli

Comments ICML 2017

Estimating Cosmological Parameters from the Dark Matter Distribution

Siamak Ravanbakhsh, Junier Oliva, Sebastien Fromenteau, Layne C. Price, Shirley Ho, Jeff Schneider, Barnabas Poczos

Comments ICML 2016

DDD17: End-To-End DAVIS Driving Dataset

Jonathan Binas, Daniel Neil, Shih-Chii Liu, Tobi Delbruck

Comments Presented at the ICML 2017 Workshop on Machine Learning for Autonomous Vehicles

K-Medoids For K-Means Seeding

James Newling, François Fleuret

Comments v1: (24 pages, 9 figures) v2: not at 33-rd ICML: forgot to modify .sty file. Reordered sections. Simplified to be specific to K-means seeding. New experiments. v3: (22 pages, 10 figures) Modified .sty file. Minor cosmetic changes. v4: added references and disussion of 2 related works v5: NIPS camera ready

Efficient Regret Minimization in Non-Convex Games

Elad Hazan, Karan Singh, Cyril Zhang

Comments Published as a conference paper at ICML 2017

Implicit Manifold Learning on Generative Adversarial Networks

Kry Yik Chau Lui, Yanshuai Cao, Maxime Gazeau, Kelvin Shuangjian Zhang

Journal ref ICML 2017 Workshop on Implicit Models