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Year Published

384 Results

August 13, 2016

Compressing Graphs and Indexes with Recursive Graph Bisection

KDD

Graph reordering is a powerful technique to increase the locality of the representations of graphs, which can be helpful in several applications. We study how the technique can be used to improve compression of graphs and inverted indexes.

By: Laxman Dhulipala, Igor Kabiljo, Brian Karrer, Giuseppe Ottaviano, Sergey Pupyrev, Alon Shalita
August 12, 2016

Towards Optimal Cardinality Estimation of Unions and Intersections with Sketches

ACM Conference on Knowledge Discovery and Data Mining

This paper presents and analyzes two new classes of methods for estimating cardinalities of intersections and unions from sketches.

By: Daniel Ting
August 11, 2016

Semi-Supervised Convolutional Networks for Translation Adaptation with Tiny Amount of In-domain Data

Conference on Natural Language Learning

We propose a method which uses semi-supervised convolutional neural networks (CNNs) to select in-domain training data for statistical machine translation.

By: Boxing Chen, Fei Huang
August 10, 2016

Neural Network-Based Word Alignment through Score Aggregation

Association for Computational Linguistics Conference on Machine Translation

We present a simple neural network for word alignment that builds source and target word window representations to compute alignment scores for sentence pairs.

By: Joel Legrand, Michael Auli, Ronan Collobert
July 27, 2016

The Relationship Between Facebook Use and Well-Being Depends on Communication Type and Tie Strength

Journal of Computer-Mediated Communication

An extensive literature shows that social relationships influence psychological well-being, but the underlying mechanisms remain unclear. We test predictions about online interactions and well-being made by theories of belongingness, relationship maintenance, relational investment, social support, and social comparison.

By: Moira Burke, Robert Kraut
July 25, 2016

Single Image 3D Interpreter Network

European Conference on Computer Vision (ECCV)

In this work, we propose 3D INterpreter Network (3D-INN), an end-to-end framework which sequentially estimates 2D keypoint heatmaps and 3D object structure, trained on both real 2D-annotated images and synthetic 3D data.

By: Antonio Torralba, Jiajun Wu, Joseph J. Lim, Joshua B. Tenenbaum, Tianfan Xue, William T. Freeman, Yuandong Tian
July 23, 2016

HapticWave: Directional Surface Vibrations using Wave-Field Synthesis

SIGGRAPH 2016

HapticWave is a novel haptic technology that delivers directional haptic sensations generated on a flat surface to the user, without requiring him/her to wear a physical device.

By: Ravish Mehra, Chris Clock, David Perek, Elia Gatti, Riccardo DeSalvo, Sean Keller
July 19, 2016

Luminescent Detector for Free-Space Optical Communication

Optica 3, 787-792 (2016)

We show that fluorescent materials can be used to increase the active area of a photodiode by orders of magnitude while maintaining its short response time and increasing its field of view.

By: Thibault Peyronel, Kevin Quirk, Tony Wang, Tobias Tiecke
June 27, 2016

Unsupervised Learning of Edges

CVPR

Data-driven approaches for edge detection have proven effective and achieve top results on modern benchmarks. However, all current data-driven edge detectors require manual supervision for training in the form of hand-labeled region segments or object boundaries.

By: Yin Li, Manohar Paluri, James M. Rehg, Piotr Dollar
June 26, 2016

End-to-End Voxel-to-Voxel Prediction

Conference on Computer Vision and Pattern Recognition (CVPR)

Over the last few years deep learning methods have emerged as one of the most prominent approaches for video analysis with most successful applications having been in the area of video classification and detection. In this paper we challenge these views by presenting a deep 3D convolutional architecture trained end to end to perform voxel-level prediction, i.e., to output a variable at every voxel of the video.

By: Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri