Papers
Firmament: Fast, Centralized Cluster Scheduling at Scale
Ionel Gog, Malte Schwarzkopf, Adam Gleave et al.
GRAPHENE: Packing and Dependency-Aware Scheduling for Data-Parallel Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao et al.
Altruistic Scheduling in Multi-Resource Clusters
Robert Grandl, Mosharaf Chowdhury, Aditya Akella et al.
Light-Weight Contexts: An OS Abstraction for Safety and Performance
James Litton, Anjo Vahldiek-Oberwagner, Eslam Elnikety et al.
Machine-Aware Atomic Broadcast Trees for Multicores
Stefan Kaestle, Reto Achermann, Roni Haecki et al.
Intermittent Computation without Hardware Support or Programmer Intervention
Joel Van Der Woude, Matthew Hicks
Push-Button Verification of File Systems via Crash Refinement
Helgi Sigurbjarnarson, James Bornholt, Emina Torlak et al.
Linguistica 5: Unsupervised Learning of Linguistic Structure
Jackson L. Lee, John A. Goldsmith
Doctor AI: Predicting Clinical Events via Recurrent Neural Networks
Edward Choi, Mohammad Taha Bahadori, Andy Schuetz et al.
A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves
Yanbo Xu, Yanxun Xu, Suchi Saria
Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics
John A Quinn, Rose Nakasi, Pius K. B. Mugagga et al.
Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series
Zachary C Lipton, David Kale, Randall Wetzel
Uncovering Voice Misuse Using Symbolic Mismatch
Marzyeh Ghassemi, Zeeshan Syed, Daryush Mehta et al.
Diagnostic Prediction Using Discomfort Drawings with IBTM
Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek et al.
Clinical Tagging with Joint Probabilistic Models
Yoni Halpern, Steven Horng, David Sontag
Mitochondria-based Renal Cell Carcinoma Subtyping: Learning from Deep vs. Flat Feature Representations
Peter J. Schüffler, Judy Sarungbam, Hassan Muhammad et al.
Learning Robust Features using Deep Learning for Automatic Seizure Detection
Pierre Thodoroff, Joelle Pineau, Andrew Lim
Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data
Truyen Tran, Wei Luo, Dinh Phung et al.
Transferring Knowledge from Text to Predict Disease Onset
Yun Liu, Collin Stultz, John Guttag et al.
gLOP: the global and Local Penalty for Capturing Predictive Heterogeneity
Rhiannon Rose, Daniel Lizotte
Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic Epilepsy
Bilal Ahmed, Thomas Thesen, Karen Blackmon et al.
Deep Survival Analysis
Rajesh Ranganath, Adler Perotte, Noémie Elhadad et al.
Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests
Narges Razavian, Jake Marcus, David Sontag
Using Kernel Methods and Model Selection for Prediction of Preterm Birth
Ilia Vovsha, Ansaf Salleb-Aouissi, Anita Raja et al.
Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data
Joseph Futoma, Mark Sendak, Blake Cameron et al.