Industry
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit
Laurence Aitchison, Lloyd Russell, Adam M. Packer, Jinyao Yan, Philippe Castonguay, Michael Hausser, Srinivas C. Turaga
Population activity measurement by calcium imaging can be combined with cellular resolution optogenetic activity perturbations to enable the mapping of neural connectivity in vivo .
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu
CNTK, are built in a centralized fashion.
Avoiding Discrimination through Causal Reasoning
Niki Kilbertus, Mateo Rojas Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, Bernhard Schölkopf
Neural Information Processing Systems http://nips.cc/
Protein Interface Prediction using Graph Convolutional Networks
Alex Fout, Jonathon Byrd, Basir Shariat, Asa Ben-Hur
Neural Information Processing Systems http://nips.cc/
Differentially Private Empirical Risk Minimization Revisited: Faster and More General
Privacy preserving is an important issue in learning.
Preventing Gradient Explosions in Gated Recurrent Units
Sekitoshi Kanai, Yasuhiro Fujiwara, Sotetsu Iwamura
Neural Information Processing Systems http://nips.cc/
Learning to Compose Domain-Specific Transformations for Data Augmentation
Alexander J. Ratner, Henry Ehrenberg, Zeshan Hussain, Jared Dunnmon, Christopher Ré
Data augmentation is a ubiquitous technique for increasing the size of labeled training sets by leveraging task-specific data transformations that preserve class labels.
Interactive Submodular Bandit
Lin Chen, Andreas Krause, Amin Karbasi
Neural Information Processing Systems http://nips.cc/
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control
Fanny Yang, Aaditya Ramdas, Kevin G. Jamieson, Martin J. Wainwright
This setup arises in many practical applications, e.g. when pharmaceutical companies test new treatment options against control pills for different diseases, or when internet companies test their
Reconstructing perceived faces from brain activations with deep adversarial neural decoding
Yağmur Güçlütürk, Umut Güçlü, Katja Seeliger, Sander Bosch, Rob van Lier, Marcel A. J. van Gerven
At the same time, the use of deep learning as the basis for neural decoding has received less widespread attention.