ICML

Configurable Markov Decision Processes

Alberto Maria Metelli, Mirco Mutti, Marcello Restelli

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

What About Applied Fairness?

Jared Sylvester, Edward Raff

Comments Accepted at Machine Learning: The Debates (ML-D), at ICML Stockholm, Sweden, 2018. 5 pages

Journal ref Machine Learning: The Debates (ML-D), at ICML Stockholm, Sweden, 2018

Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning

Luca Franceschi, Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo, Paolo Frasconi

Comments This submission is a reduced version of (Franceschi et al., arXiv:1806.04910) which has been accepted at the main ICML 2018 conference. In this paper we illustrate the software framework, material that could not be included in the conference paper

Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity

Lin Chen, Christopher Harshaw, Hamed Hassani, Amin Karbasi

Comments Accepted by ICML 2018

Learning to Explain: An Information-Theoretic Perspective on Model Interpretation

Jianbo Chen, Le Song, Martin J. Wainwright, Michael I. Jordan

Comments Accepted to ICML 2018 as a long oral

Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace

Yoonho Lee, Seungjin Choi

Comments Accepted to ICML 2018

Learning Deep ResNet Blocks Sequentially using Boosting Theory

Furong Huang, Jordan Ash, John Langford, Robert Schapire

Comments Accepted to ICML 2018

Hierarchical Long-term Video Prediction without Supervision

Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee

Comments International Conference on Machine Learning (ICML) 2018

Safe learning-based optimal motion planning for automated driving

Zlatan Ajanovic, Bakir Lacevic, Georg Stettinger, Daniel Watzenig, Martin Horn

Comments 3 pages, 1 figure, 1 pseudocode, extended abstract accepted to ICML / IJCAI / AAMAS 2018 Workshop on Planning and Learning (PAL-18)

One-Shot Segmentation in Clutter

Claudio Michaelis, Matthias Bethge, Alexander S. Ecker

Comments To appaer in: $\textit{Proceedings of the $\mathit{35}^{th}$ International Conference on Machine Learning}$, Stockholm, Sweden, PMLR 80, 2018

Learning Longer-term Dependencies in RNNs with Auxiliary Losses

Trieu H. Trinh, Andrew M. Dai, Minh-Thang Luong, Quoc V. Le

Comments ICML 2018

Active Learning with Logged Data

Songbai Yan, Kamalika Chaudhuri, Tara Javidi

Comments ICML 2018

Bandits with Delayed, Aggregated Anonymous Feedback

Ciara Pike-Burke, Shipra Agrawal, Csaba Szepesvari, Steffen Grunewalder

Comments ICML 2018

Improving Regression Performance with Distributional Losses

Ehsan Imani, Martha White

Comments 12 pages, 4 figures. To appear in Proceedings of the 35th International Conference on Machine Learning, 2018

Using Inherent Structures to design Lean 2-layer RBMs

Abhishek Bansal, Abhinav Anand, Chiranjib Bhattacharyya

Comments ICML 2018 (Full Paper + Long Talk)

Focused Hierarchical RNNs for Conditional Sequence Processing

Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Chris Pal

Comments To appear at ICML 2018

Learning to Speed Up Structured Output Prediction

Xingyuan Pan, Vivek Srikumar

Comments International Conference on Machine Learning, Stockholm, Sweden, 2018

Efficient end-to-end learning for quantizable representations

Yeonwoo Jeong, Hyun Oh Song

Comments Accepted and to appear at ICML 2018. Camera ready version

Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees

Adrien Taylor, Bryan Van Scoy, Laurent Lessard

Comments to appear in ICML'18

Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing---and Back

Elliot Meyerson, Risto Miikkulainen

Comments Published as a conference paper at ICML 2018; 10 pages

The Weighted Kendall and High-order Kernels for Permutations

Yunlong Jiao, Jean-Philippe Vert

Comments Published in ICML 2018

Kernel Recursive ABC: Point Estimation with Intractable Likelihood

Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki, Kenji Fukumizu

Comments to appear in ICML 2018. 18 pages

Differentially Private Matrix Completion Revisited

Prateek Jain, Om Thakkar, Abhradeep Thakurta

Comments Updated version. Accepted for presentation at International Conference on Machine Learning (ICML) 2018

Learning Representations and Generative Models for 3D Point Clouds

Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, Leonidas Guibas

Journal ref 35th International Conference on Machine Learning (ICML), 2018

Autoregressive Convolutional Neural Networks for Asynchronous Time Series

Mikołaj Bińkowski, Gautier Marti, Philippe Donnat

Comments Proceedings of The 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, 2018, to appear

Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs

Bin Hu, Stephen Wright, Laurent Lessard

Comments to appear at ICML 2018

Conditional Noise-Contrastive Estimation of Unnormalised Models

Ciwan Ceylan, Michael U. Gutmann

Comments Accepted to ICML 2018

An Estimation and Analysis Framework for the Rasch Model

Andrew S. Lan, Mung Chiang, Christoph Studer

Comments To be presented at ICML 2018

Linear Spectral Estimators and an Application to Phase Retrieval

Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer

Comments To appear at ICML 2018, extended version with supplementary material

Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction

Siyuan Qi, Baoxiong Jia, Song-Chun Zhu

Comments ICML 2018