On Discriminative vs. Generative Classifiers: A …

SAGA: A Fast Incremental Gradient Method With Support for ...

SAGA is preferred over SVRG both theoretically and in practice. For neural networks, where no theory is available for either method, the storage of gradients is generally more expensive than the

  With, Methods, Support, Fast, Saga, Derating, Incremental, A fast incremental gradient method with support

Thinking Fast and Slow with Deep Learning and Tree Search

System 1 is a fast, unconscious and automatic mode of thought, also known as intuition or heuristic process. System 2, an evolutionarily recent process unique to humans, is a slow, conscious, explicit

  With, Learning, Search, Tree, Thinking, Deep, Fast, Slow, Thinking fast and slow with deep learning and tree search

A Growing Neural Gas Network Learns Topologies

A Growing Neural Gas Network Learns Topologies 627 a) Delaunay triangulation b) induced Delaunay triangulation Figure 1: Two ways of defining closeness among a set of points.

  Network, Neural, Topologies, Neural gas network

Attention is All you Need - Neural Information Processing ...

Attention Is All You Need Ashish Vaswani Google Brain avaswani@google.com Noam Shazeer Google Brain noam@google.com Niki Parmar Google Research nikip@google.com

  Needs, Attention, Neural, Attention is all you need

ImageNet Classification with Deep Convolutional Neural ...

Challenge, an annual competition called the ImageNet Large-Scale Visual Recognition Challenge (ILSVRC) has been held. ILSVRC uses a subset of ImageNet with roughly 1000 images in each of 1000 categories. In all, there are roughly 1.2 million training images, 50,000 validation images, and 150,000 testing images. ILSVRC-2010 is the only version ...

  Challenges, Scale, Visual, Recognition, Ilsvrc, Scale visual recognition challenge

Generative Adversarial Nets - NIPS

Generative adversarial networks has been sometimes confused with the related concept of “adversar-ial examples” [28]. Adversarial examples are examples found by using gradient-based optimization directly on the input to a classification network, in order to find examples that are similar to the data yet misclassified.

  Network, Adversarial, Generative, Generative adversarial, Generative adversarial networks, Adversar ial, Adversar

Time-series Generative Adversarial Networks

A good generative model for time-series data should preserve temporal dynamics, in the sense that new sequences respect the original relationships between variables across time. Existing methods that bring generative adversarial networks (GANs) into the sequential setting do not adequately attend to the temporal correlations unique to time ...

  Network, Adversarial, Generative, Generative adversarial networks

Hidden Technical Debt in Machine Learning Systems

account for in system design. These include boundary erosion, entanglement, hidden feedback loops, undeclared consumers, data dependencies, configuration issues, changes in the external world, and a variety of system-level anti-patterns. 1 Introduction As the machine learning (ML) community continues to accumulate years of experience with live

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Character-level Convolutional Networks for Text Classification

Applying convolutional networks to text classification or natural language processing at large was explored in literature. It has been shown that ConvNets can be directly applied to distributed [6] [16] or discrete [13] embedding of words, without any knowledge on the syntactic or semantic structures of a language.

  Network, Convolutional, Convolutional networks, Semantics

InfoGAN: Interpretable Representation Learning by ...

30th Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain. ... a higher-order extension of the spike-and-slab restricted Boltzmann machine that can disentangle emotion from identity on the Toronto Face Dataset ... we want PG(cjx) to have a small entropy. In other words, the information in the latent code cshould not ...

  Information, Neural, Entropy, Spike, Neural information

United States real-world drug utilization patterns …

United States real-world drug utilization patterns and associated overall survival in Medicare patients with newly-diagnosed metastatic triple negative breast cancer using

The Socio-Economic and Demographic …

351 South Asian Studies A Research Journal of South Asian Studies Vol. 24, No. 2, July 2009, pp. 351-367 The Socio-Economic and Demographic Determinants

  Economic, Determinants, Demographic, Socio, Socio economic and demographic, Socio economic and demographic determinants

Lecture 10: Logistical Regression II— Multinomial …

Lecture 10: Logistical Regression II— Multinomial Data Prof. Sharyn O’Halloran Sustainable Development U9611 Econometrics II

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Gaussian Processes for Machine Learning

C. E. Rasmussen & C. K. I. Williams, Gaussian Processes for Machine Learning, the MIT Press, 2006, ISBN 026218253X. 2006 Massachusetts Institute of Technology.c www.GaussianProcess.org/gpml

  Processes, Machine, Learning, Gaussian processes for machine learning, Gaussian

A.1 SAS EXAMPLES - Department of Statistics

A.1 SAS EXAMPLES SAS is general-purpose software for a wide variety of statistical analyses. The main procedures (PROCs) for categorical data analyses are FREQ, GENMOD, LOGISTIC,

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