21.06.16 1:07:55 Market-Oriented Cloud Computing and Big Data Applications
Computing is being transformed to a model consisting of services that are commoditized and delivered in a manner similar to utilities such as water, electricity, gas, and telephony.
2 094
36.4
21.06.16 1:30:02 Modeling high-dimensional sequences with recurrent neural networks
Humans commonly understand sequential events by giving importance to what they expect rather than exclusively to what they actually observe.
2 293
36
21.06.16 1:14:34 In Systems We Trust
Computing has advanced to the point where users are often not even aware of the systems they implicitly trust, much less whether those systems deserve that trust.
43
21.06.16 1:16:26 3rd Pacific Northwest Regional NLP Workshop: Introduction & Long Talks
9:30 Introduction Blitz Long Talks: 10:00 Context-dependent Semantic Parsing for Time Expressions, Kenton Lee, Yoav Artzi, Jesse Dodge and Luke Zettlemoyer 10:20 Query-based Abstractive
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55.3
21.06.16 1:23:06 Programmer, Interrupted: Data, Brains, and Tools
Despite its vast capacity and associative powers, the human brain does not deal well with interruptions.
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21.06.16 55:13 Steps toward usable verification
First, I will provide some background information on CodeContracts, the language-agnostic specification language of .NET 4.x, and on Clousot, the companion abstract interpretation-based verifier.
49
21.06.16 1:06:24 Cloudlets for Mobile Computing
Resource poverty is a fundamental constraint that severely limits the class of applications that can be run on mobile devices.
2 307
47.7
21.06.16 1:27:28 Science in the Cloud
The sciences are currently undergoing a fundamental transition due to the avalanche of data that is generated by instruments, simulations, on-line archives and social media.
19
21.06.16 26:59 LampsonFest - Adam Kalai, Closing Remarks
Adam Kalai - A Colorful Approach to Programming by Example
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21.06.16 1:00:00 New Perspectives on Machine Learning and Science
This session will look into the latest advances in areas of machine learning, such as causality, while also reviewing our understanding of topics such as deep learning.
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21.06.16 1:04:01 Statistical Text Analysis for Social Science
What can text analysis tell us about society? Corpora of news, books, and social media encode human beliefs and culture.
4 359
33.4
21.06.16 1:06:47 Mechanism Design and Economic Inference
The promise of data science is that system data can be analyzed and its understanding can be used to improve the system (i.e., to obtain good outcomes).
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21.06.16 55:51 Rethinking Machine Learning In The 21st Century: From Optimization To Equilibration
The past two decades has seen machine learning (ML) transformed from an academic curiosity to a multi-billion dollar industry, and a centerpiece of our economic, social, scientific, and security
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15.4
21.06.16 37:21 Making Machine Learning Reproducible with CodaLab
We often come across work in Machine Learning which is difficult to reproduce because either the parameters used were not reported in the literature or the experiment setup was not the same.
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68.5
21.06.16 1:00:16 Using ConvNets, MALIS and crowd-sourcing to map the retinal connectome
Neural circuits in the brain are formed from neurons connecting to one another in highly structured ways.
43
21.06.16 1:17:09 Scalable Recognition of Human Activities for Pervasive Applications in Natural Environments
Past approaches on the automatic recognition of human activities have achieved promising results by sensing patterns of physical motion via wireless accelerometers worn on the body and classifying
71
21.06.16 1:23:30 Program Synthesis for the Masses
New computing platforms have greatly increased the demand for programmers, but learning to program remains a big challenge.
1 986
19.7
21.06.16 1:36:36 Symmetry-Based Learning
Learning representations is arguably the central problem in machine learning, and symmetry group theory is a natural foundation for it.
2 320
13.4
21.06.16 25:24 Torch
The goal of this workshop is to inform people about open source machine learning systems being developed, aid the coordination of such projects, and discuss future plans.
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21.06.16 26:58 Vowpal Wabbit
The goal of this workshop is to inform people about open source machine learning systems being developed, aid the coordination of such projects, and discuss future plans.
6 165
27.8
21.06.16 1:08:21 Visual Nearest Neighbor Search
Template Matching finds the best match in an image to a given template and this is used in a variety of computer vision applications. I will discuss several extensions to Template Matching.
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29.4
21.06.16 1:01:57 Data Driven Student Feedback For MOOCs: Global Scale Education for the 21st century
In recent years an increasing number of students have turned to online resources, such as massive open online courses (MOOCs) for learning.
43
21.06.16 31:43 Stan
The goal of this workshop is to inform people about open source machine learning systems being developed, aid the coordination of such projects, and discuss future plans.
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21.06.16 1:00:35 Robust Probabilistic Inference
Probabilistic Inference is the task of given a certain set of observations, to deduce the probability of various outcomes. This is a very basic task both in statistics and in machine learning.
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21.06.16 1:32:25 Deep Learning for Text Processing
Deep learning has enjoyed tremendous success in recent years in speech and visual object recognition, as well as in language processing (although to somewhat less extent).
2 333
77.4
21.06.16 22:02 Shogun
The goal of this workshop is to inform people about open source machine learning systems being developed, aid the coordination of such projects, and discuss future plans.
90
21.06.16 1:01:08 3rd Pacific Northwest Regional NLP Workshop: Short Talks
Short Talks 11:20 Approximate Parsing with “Hedge Grammars”, Mahsa Yarmohammadi 11:32 Context Representation for Named Entity Linking, Xiao Ling, Sameer Singh and Daniel S.
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21.06.16 52:22 Theory and Methods for Recovering Structured Patterns in High Dimensional Data
Regression with a sparsity constraint plays a vital role in many machine learning and signal processing applications.
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23.2
21.06.16 1:00:44 Sparse Stochastic Bandits
Many learning problems, such as choosing which ad to put on a website, or what movie to recommend to a user, can be cast as stochastic bandit problems.
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26.8
21.06.16 46:26 Representation, Modeling and Computation: Opportunities and Challenges of Modern Datasets
Machine learning from modern datasets presents novel opportunities and challenges.
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