ICML

Consistent Individualized Feature Attribution for Tree Ensembles

Scott M. Lundberg, Gabriel G. Erion, Su-In Lee

Comments Follow-up to 2017 ICML Workshop arXiv:1706.06060

Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation

Antreas Antoniou, Amos Storkey

Comments Work in Progress - Under Review in ICML 2019

Tighter Variational Bounds are Not Necessarily Better

Tom Rainforth, Adam R. Kosiorek, Tuan Anh Le, Chris J. Maddison, Maximilian Igl, Frank Wood, Yee Whye Teh

Comments To appear at ICML 2018

Automated Model Selection with Bayesian Quadrature

Henry Chai, Jean-Francois Ton, Roman Garnett, Michael A. Osborne

Comments 10 pages, 5 figures. Currently in submission to ICML 2019

MAGAN: Aligning Biological Manifolds

Matthew Amodio, Smita Krishnaswamy

Journal ref Proceedings of the 35th International Conference on Machine Learning, PMLR 80:215-223, 2018

Essentially No Barriers in Neural Network Energy Landscape

Felix Draxler, Kambis Veschgini, Manfred Salmhofer, Fred A. Hamprecht

Comments In Proceedings of 35th International Conference on Machine Learning (ICML 2018)

Journal ref Proceedings of the 35th International Conference on Machine Learning, PMLR 80:1308-1317, 2018

Machine Learning Algorithms for Classification of Microcirculation Images from Septic and Non-Septic Patients

Perikumar Javia, Aman Rana, Nathan Shapiro, Pratik Shah

Comments Accepted for publication at 2018 IEEE International Conference on Machine Learning and Applications (IEEE ICMLA)

Computational Histological Staining and Destaining of Prostate Core Biopsy RGB Images with Generative Adversarial Neural Networks

Aman Rana, Gregory Yauney, Alarice Lowe, Pratik Shah

Comments Accepted for publication at 2018 IEEE International Conference on Machine Learning and Applications (ICMLA)

Differentially Private Continual Learning

Sebastian Farquhar, Yarin Gal

Comments Presented at the Privacy in Machine Learning and AI workshop at ICML 2018

Sinkhorn Divergence of Topological Signature Estimates for Time Series Classification

Colin Stephen

Comments 9 pages, 4 figures, 2018 17th International Conference on Machine Learning and Applications

Contrastive Variational Autoencoder Enhances Salient Features

Abubakar Abid, James Zou

Comments Submitted to ICML 2019

Dropout is a special case of the stochastic delta rule: faster and more accurate deep learning

Noah Frazier-Logue, Stephen José Hanson

Comments 6 pages, 7 figures; submitted to ICML

On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

Abien Fred Agarap

Comments 5 pages, 5 figures, 2 tables, presented at the International Conference on Machine Learning and Soft Computing (ICMLSC) 2018 in Phu Quoc Island, Viet Nam

A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic Data

Abien Fred Agarap

Comments 5 pages, 4 figures, 5 tables, accepted paper at the International Conference on Machine Learning and Computing (ICMLC) 2018

PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

Paavo Parmas, Carl Edward Rasmussen, Jan Peters, Kenji Doya

Comments ICML 2018

Learning to Fingerprint the Latent Structure in Question Articulation

Kumar Mrityunjay, Guntur Ravindra

Comments Pre-Print, ACCEPTED FOR PRESENTATION AT the 17th IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA2018)

Concrete Autoencoders for Differentiable Feature Selection and Reconstruction

Abubakar Abid, Muhammad Fatih Balin, James Zou

Comments Submitted to ICML 2019

Avoiding Latent Variable Collapse With Generative Skip Models

Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei

Comments In the Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), Naha, Okinawa, Japan. PMLR: Volume 89. An earlier version of this paper was presented at the Workshop on Theoretical Foundations and Applications of Deep Generative Models, ICML, 2018

Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement

André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel Mankowitz, Augustin Žídek, Rémi Munos

Comments Published at ICML 2018

Towards Fair Deep Clustering With Multi-State Protected Variables

Bokun Wang, Ian Davidson

Comments under review as a conference paper at icml 2019

Designing a Multi-Objective Reward Function for Creating Teams of Robotic Bodyguards Using Deep Reinforcement Learning

Hassam Ullah Sheikh, Ladislau Bölöni

Comments Accepted at the 1st Workshop on Goal Specifications for Reinforcement Learning at ICML 2018

The Emergence of Complex Bodyguard Behavior Through Multi-Agent Reinforcement Learning

Hassam Ullah Sheikh, Ladislau Bölöni

Comments Accepted at Autonomy in Teams Workshop at ICML 2018

Information-Theoretic Understanding of Population Risk Improvement with Model Compression

Yuheng Bu, Weihao Gao, Shaofeng Zou, Venugopal V. Veeravalli

Comments submitted to ICML 2019

Graph Neural Networks for Learning Robot Team Coordination

Amanda Prorok

Comments Presented at the Federated AI for Robotics Workshop, IJCAI-ECAI/ICML/AAMAS 2018

Journal ref Federated AI for Robotics Workshop, IJCAI-ECAI/ICML/AAMAS 2018

A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization

Robin Vogel, Aurélien Bellet, Stéphan Clémençon

Comments 8 pages main paper, 22 pages with appendices, proceedings of ICML 2018

Journal ref PMLR 80 (2018) 5062-5071

Similarity Learning for Provably Accurate Sparse Linear Classification

Aurelien Bellet, Amaury Habrard, Marc Sebban

Comments Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)

A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data

Yining Wang, Yu-Xiang Wang, Aarti Singh

Comments 40 pages, 2 figures. A shorter version of this paper titled "A Deterministic Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data" with partial results appeared at Proceedings of the 32nd International Conference on Machine Learning (ICML) held at Lille, France in 2015

Journal ref IEEE Transactions on Information Theory, 65(2):685-706, 2019

DeepDrum: An Adaptive Conditional Neural Network

Dimos Makris, Maximos Kaliakatsos-Papakostas, Katia Lida Kermanidis

Comments 2018 Joint Workshop on Machine Learning for Music. The Federated Artificial Intelligence Meeting (FAIM), a joint workshop program of ICML, IJCAI/ECAI, and AAMAS

Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks

Alexey Shvets, Vladimir Iglovikov, Alexander Rakhlin, Alexandr A. Kalinin

Comments 12 pages, 6 figures

Journal ref 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)

Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning

Alexey Shvets, Alexander Rakhlin, Alexandr A. Kalinin, Vladimir Iglovikov

Comments 9 pages, 3 figures. arXiv admin note: substantial text overlap with arXiv:1804.08024

Journal ref 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)