Research Area
Year Published

669 Results

June 6, 2017

Analysis of Effective Impedance Transmitted to the Operator in Position-Exchange Bilateral Teleoperation

IEEE World Haptics 2017

In this paper, we analyze the impedance transmitted to the operator in bilateral teleoperation including the effects of master and slave dynamics, local and communication time delay, low-pass filtering of the velocity estimate, and controller stiffness and damping, for three different environment dynamics: free, clamped, and a mass-damper-spring.

By: Nick Colonnese, Allison M. Okamura
Areas: AR/VR

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

Learning End-to-End Goal-Oriented Dialog

International Conference on Learning Representations (ICLR)

This paper proposes a testbed to break down the strengths and shortcomings of end-to-end dialog systems in goal-oriented applications.

By: Antoine Bordes, Y-Lan Boureau, Jason Weston