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Year Published

388 Results

December 4, 2017

VAIN: Attentional Multi-agent Predictive Modeling

Neural Information Processing Systems (NIPS)

In this paper we introduce VAIN, a novel attentional architecture for multi-agent predictive modeling that scales linearly with the number of agents. Multi-agent predictive modeling is an essential step for understanding physical, social and team-play systems.

By: Yedid Hoshen
December 4, 2017

Gradient Episodic Memory for Continual Learning

Neural Information Processing Systems (NIPS)

One major obstacle towards AI is the poor ability of models to solve new problems quicker, and without forgetting previously acquired knowledge. To better understand this issue, we study the problem of continual learning, where the model observes, once and one by one, examples concerning a sequence of tasks.

By: David Lopez-Paz, Marc'Aurelio Ranzato
December 4, 2017

Poincaré Embeddings for Learning Hierarchical Representations

Neural Information Processing Systems (NIPS)

In this work, we introduce a new approach for learning hierarchical representations of symbolic data by embedding them into hyperbolic space – or more precisely into an n-dimensional Poincaré ball.

By: Maximilian Nickel, Douwe Kiela
November 27, 2017

Fast Gaze-Contingent Optimal Decompositions for Multifocal Displays

SIGGRAPH ASIA

Our goal is to enable interactive optimal decomposition algorithms capable of driving a vergence- and accommodation-tracked multifocal testbed. Ultimately, such a testbed is necessary to establish the requirements for the practical use of multifocal displays, in terms of computational demand and hardware accuracy. To this end, we present an efficient algorithm for optimal decompositions, incorporating insights from vision science.

By: Oliver Mercier, Yusufu Sulai, Kevin Mackenzie, Marina Zannoli, James Hillis, Derek Nowrouzezahrai, Douglas Lanman
Areas: AR/VR
November 27, 2017

Casual 3D Photography

SIGGRAPH ASIA

We present an algorithm that enables casual 3D photography. Given a set of input photos captured with a hand-held cell phone or DSLR camera, our algorithm reconstructs a 3D photo, a central panoramic, textured, normal mapped, multi-layered geometric mesh representation. Our geometric representation also allows interacting with the scene using 3D geometry-aware effects, such as adding new objects to the scene and artistic lighting effects.

By: Suhib Alsisan, Richard Szeliski, Johannes Kopf
November 27, 2017

Bringing Portraits to Life

SIGGRAPH ASIA

We present a technique to automatically animate a still portrait, making it possible for the subject in the photo to…

By: Hadar Averbuch-Elor, Daniel Cohen-Or, Johannes Kopf, Michael Cohen
November 14, 2017

Fine Pointing Concepts for Optical Intersatellite Links

International Conference on Space Optical Systems (ICSOS)

In this paper we present two fine pointing architectures that support high-accuracy pointing, while also featuring simplification of the small-space optical assembly hardware, reduction in the number and complexity of constituent components, full self-calibration capability, and relaxation of otherwise-strict, cost-driving subassembly requirements.

By: Eric Miller, Kevin Birnbaum, Chien-Chung Chen, Andrew Grier, Matt Hunwardsen, Dominic Jandrain
November 1, 2017

High-Resolution Measurement of Data Center Microbursts

ACM Internet Measurement Conference

In this study, we explore the fine-grained behaviors of a large production data center using extremely highresolution measurements (10s to 100s of microsecond) of rack-level traffic. Our results show that characterizing network events like congestion and synchronized behavior in data centers does indeed require the use of such measurements.

By: Qiao Zhang, Vincent Liu, James Hongyi Zeng, Arvind Krishnamurthy
November 1, 2017

An Empirical Characterization of IFTTT: Ecosystem, Usage, and Performance

ACM Internet Measurement Conference 2017

IFTTT is a popular trigger-action programming platform whose applets can automate more than 400 services of IoT devices and web applications. We conduct an empirical study of IFTTT using a combined approach of analyzing data collected for 6 months and performing controlled experiments using a custom testbed.

By: Xianghang Mi, Feng Qian, Ying Zhang, XiaoFeng Wang
October 30, 2017

Crowd Intelligence Enhances Automated Mobile Testing

Automated Software Engineering Conference (ASE)

In this paper we show that information extracted from crowdbased testing can enhance automated mobile testing and introduce POLARIZ, which generates replicable test scripts from crowd-based testing, extracting cross-app ‘motif’ events.

By: Ke Mao, Mark Harman, Yue Jia