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444 Results

May 31, 2017

Modout: Learning Multi-modal Architectures by Stochastic Regularization

IEEE Conference on Automatic Face and Gesture Recognition (FG 2017)

This paper describes Modout, a model selection method based on stochastic regularization, which is particularly useful in the multi-modal setting.

By: Fan Li, Natalia Neverova, Christian Wolf, Graham Taylor
May 30, 2017

Sensors for Future VR Applications

International Image Sensor Workshop (IISW)

In this paper, we provide examples of some tracking and mapping functions of virtual reality sensors that illustrate the critical requirements and performance metrics. The sensor performance, form factor, power, and data bandwidth are the main challenges in a battery powered, always on VR devices.

By: Chiao Liu, Michael Hall, Renzo De Nardi, Nicholas Trail, Richard Newcombe
May 22, 2017

IVD: Automatic Learning and Enforcement of Authorization Rules in Online Social Networks

IEEE Symposium on Security and Privacy (IEEE S&P)

In this paper, we propose Invariant Detector (IVD), a defense-in-depth system that automatically learns authorization rules from normal data manipulation patterns and distills them into likely invariants.

By: Paul Marinescu, Chad Parry, Marjori Pomarole, Yuan Tian, Patrick Tague, Ioannis Papagiannis
May 21, 2017

CAN: Creative Adversarial Networks

IEEE International Conference on Communications (ICCC)

We propose a new system for generating art. The system generates art by looking at art and learning about style; and becomes creative by increasing the arousal potential of the generated art by deviating from the learned styles. We build over Generative Adversarial Networks (GAN), which have shown the ability to learn to generate novel images simulating a given distribution.

By: Ahmed Elgammal, Bingchen Liu, Mohamed Elhoseiny, Marian Mazzone
May 16, 2017

Cultural Diffusion and Trends in Facebook Photographs

The International AAAI Conference on Web and Social Media (ICWSM)

Online social media is a social vehicle in which people share various moments of their lives with their friends, such as playing sports, cooking dinner or just taking a selfie for fun, via visual means, i.e., photographs. Our study takes a closer look at the popular visual concepts illustrating various cultural lifestyles from aggregated, de-identified photographs.

By: Quenzeng You, Dario Garcia, Manohar Paluri, Jiebo Luo, Jungseock Joo
May 6, 2017

Paradigm shift from Human Computer Interaction to Integration

Computer Human Interaction (CHI)

In 1960, JCR Licklider forecast three phases: human- computer interaction, human-computer symbiosis, and ultra-intelligent machines. Human-computer symbiosis or what we call “integration” is already well under way. This SIG will discuss how the CHI community should think about the paradigm shift from interaction to integration as designers, practitioners, researchers, and as a society.

By: Umer Farooq, Jonathan T. Grudin
May 2, 2017

Better Computer Go Player with Neural Network and Long-Term Prediction

International Conference on Learning Representations (ICLR)

Competing with top human players in the ancient game of Go has been a longterm goal of artificial intelligence. Recent works [Maddison et al. (2015); Clark & Storkey (2015)] show that search is not strictly necessary for machine Go players. A pure pattern-matching approach, based on a Deep Convolutional Neural Network (DCNN) that predicts the next move, can perform as well as Monte Carlo Tree Search (MCTS)-based open source Go engines such as Pachi [Baudis & Gailly (2012)] if its search budget is limited. We extend this idea in our bot named darkforest, which relies on a DCNN designed for long-term predictions.

By: Yuandong Tian, Yan Zhu
April 27, 2017

Passive Realtime Datacenter Fault Detection

USENIX Symposium on Networked Systems Design and Implementation (NSDI) 2017

We describe how to expedite the process of detecting and localizing partial datacenter faults using an end-host method generalizable to most datacenter applications.

By: Arjun Roy, James Hongyi Zeng, Jasmeet Bagga, Alex C. Snoeren
April 24, 2017

Training Agent for First-Person Shooter Game With Actor-Critic Curriculum Learning

International Conference on Learning Representations (ICLR) 2017

In this paper, we propose a new framework for training vision-based agent for First-Person Shooter (FPS) Game, in particular Doom.

By: Yuxin Wu, Yuandong Tian
April 24, 2017

Unsupervised Cross-Domain Image Generation

International Conference on Learning Representations (ICLR) 2017

We study the problem of transferring a sample in one domain to an analog sample in another domain. Given two related domains, S and T, we would like to learn a generative function G that maps an input sample from S to the domain T, such that the output of a given representation function f, which accepts inputs in either domains, would remain unchanged.

By: Yaniv Taigman, Adam Polyak, Lior Wolf