MLconf SF 2019 Speaker Resources:
Franziska Bell, Director of Data Science, Head of Platform Data Science, Uber
Uber’s Intelligent Insights Assistant
- Deep and Confident Prediction for Time Series at Uber: https://arxiv.org/pdf/1709.
01907.pdf - Engineering Extreme Event Forecasting at Uber with Recurrent Neural Networks: eng.uber.com/neural-
networks/ - Omphalos, Uber’s Parallel and Language Extensible Time Series Backtesting Tool: eng.uber.com/omphalos/
- Engineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber: https://eng.uber.com/neural-
networks-uncertainty- estimation/ - Improving Driver Communication through One-Click Chat, Uber’s Smart Reply System: https://eng.uber.com/one-
click-chat/
Mihajlo Grbovic, Principal Machine Learning Scientist, Airbnb
Machine Learning-Powered Search Ranking of Airbnb Experiences
Vito Ostuni, Pandora
‘The Voice’: New Challenges in a Zero UI world
Anoop Deoras, Researcher, Netflix
Building an Incrementally Trained, Local Taste Aware, Global Deep Learned Recommender System Model
Sneha Rajana, Software Development Engineer, Amazon
Deep Learning Architectures for Semantic Relation Detection Tasks
- https://www.aclweb.org/anthology/S17-1002.pdf
- https://github.com/srajana/AntNET
- https://github.com/vered1986/LexNET
- https://arxiv.org/pdf/1608.05014.pdf
- https://arxiv.org/abs/1610.08694
- https://arxiv.org/pdf/1906.05612.pdf
- https://arxiv.org/pdf/1906.04706.pdf
- https://arxiv.org/abs/1810.04805
- https://arxiv.org/abs/1706.03762
- https://www.aclweb.org/anthology/P19-1279.pdf
- https://arxiv.org/pdf/1905.08284.pdf
- https://arxiv.org/abs/1901.08163
- https://www.aclweb.org/anthology/P16-1123/
June Andrews, AI Instruments, Stitch Fix
The Uncanny Valley of ML
Noam Finkelstein, PhD student, Johns Hopkins University
The Importance of Modeling Data Collection
Meghana Ravikumar, Platform Engineering Lead, SigOpt
Optimized Image Classification on the Cheap
Martin Isaksson, CEO and Co-founder, PerceptiLabs
How to enable warp speed for Machine Learning modeling
Ted Willke, Director of the Brain-Inspired Computing Lab, Intel
The Brain’s Guide to Dealing with Context in Language Understanding
Anitha Kannan & Xavier Amatriain, Founding Member & CTO, Curai
AI for healthcare: Scaling Access and Quality of Care for Everyone
Jekaterina Novikova, Director of Machine Learning, Winterlight Labs
Machine Learning Methods in Detecting Alzheimer’s Disease from Speech and Language
- Z. Zhu, J. Novikova, and F. Rudzicz. Detecting cognitive impairments by agreeing on interpretations of linguistic features. In Proceedings of NAACL, 2019
- J. Novikova, A. Balagopalan, K. Shkaruta and F. Rudzicz. Lexical Features Are More Vulnerable, Syntactic Features Have More Predictive Power. In: The 5th Workshop on Noisy User-generated Text at EMNLP, Hong Kong, 2019
- Z. Zhu, J. Novikova, and F. Rudzicz. Semi-supervised classification by reaching consensus among modalities. In: NeurIPS Workshop on Interpretability and Robustness in Audio, Speech, and Language IRASL, Montreal, 2018
Vinay Prabhu, Chief Scientist, UnifyID Inc
Project GaitNet: Ushering in the ImageNet moment for human Gait kinematics
Papers:
- [1] Stephanie Tietz, Vinay Uday Prabhu, ‘GaitID-2-SquatID: Deep transfer learning for human kinematics’, Time Series workshop, ICML-2019, June-2019, Long Beach, California, USA
- [2] Vinay Prabhu, Stephanie Tietz and Anh Ta, ‘Classifying humans using Deep time-series transfer learning : accelerometric gait-cycles to gyroscopic squats , Proceedings, 5th SIGKDD Workshop on Mining and Learning from Time Series (MiLeTS), KDD-2019, Anchorage, Aug-2019, Alaska
- [3] Vinay Prabhu, John Whaley and Mihail D, ‘MODHILL: A framework for debugging gait in multi-factor authentication systems’, Workshop on Human In the Loop Learning (HILL)-ICLR 2019, May 2019, New Orleans, USA
- [4] Vinay Prabhu, John Whaley ,”Vulnerability of deep learning-based gait biometric recognition to adversarial perturbations”, In Proceedings of the CVPR 2017 CV-COPS workshop, 2017,Honolulu, Hawaii — July 21, 2017.
Code and Datasets:
Further reading list of 3 other notable Gait-classification projects:
- IDNet: https://arxiv.org/pdf/1606.03238.pdf
- Abacus: http://ieeexplore.ieee.org/ielx7/6287639/7419931/07458136.pdf?tp=&arnumber=7458136&isnumber=7419931
- DeepSense:https://arxiv.org/pdf/1611.01942.pdf
Josh Wills, Software Engineer, Slack
Data Labeling as Religious Experience
Igor Markov, Professor, University of Michigan
Quantum Computing: a Treasure Hunt, not a Gold Rush
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Quantum Supremacy Is Both Closer and Farther than It Appears
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Quantum supremacy using a programmable superconducting processor
