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June 25, 2018

Do Diffusion Protocols Govern Cascade Growth?

International AAAI Conference on Web and Social Media (ICWSM)

Large cascades can develop in online social networks as people share information with one another. Though simple reshare cascades have been studied extensively, the full range of cascading behaviors on social media is much more diverse. Here we study how diffusion protocols, or the social exchanges that enable information transmission, affect cascade growth, analogous to the way communication protocols define how information is transmitted from one point to another.

By: Justin Cheng, Jon Kleinberg, Jure Leskovec, David Liben-Nowell, Bogdan State, Karthik Subbian, Lada Adamic
June 25, 2018

HALE Multidisciplinary Design Optimization Part I: Solar-Powered Single and Multiple-Boom Aircraft

AIAA Aviation

In this paper (Part I), optimization case studies for single and dual-boom configurations are discussed.

By: Dorian F. Colas, Nicholas H. Roberts, Vishvas S. Suryakumar
June 20, 2018

HHVM JIT: A Profile-Guided, Region-Based Compiler for PHP and Hack

Programming Language Design and Implementation (PLDI)

This paper describes the design of the second generation of the HHVM JIT and how it addresses the challenges to efficiently execute PHP and Hack programs. This new design uses profiling to build an aggressive region-based JIT compiler. We discuss the benefits of this approach compared to the more popular method-based and trace-based approaches to compile dynamic languages.

By: Guilherme Ottoni
June 19, 2018

LAMV: Learning to align and match videos with kernelized temporal layers

Computer Vision and Pattern Recognition (CVPR)

This paper considers a learnable approach for comparing and aligning videos. Our architecture builds upon and revisits temporal match kernels within neural networks: we propose a new temporal layer that finds temporal alignments by maximizing the scores between two sequences of vectors, according to a time-sensitive similarity metric parametrized in the Fourier domain.

By: Lorenzo Baraldi, Matthijs Douze, Rita Cucchiara, Hervé Jégou
June 19, 2018

Link and code: Fast indexing with graphs and compact regression codes

Computer Vision and Pattern Recognition (CVPR)

Similarity search approaches based on graph walks have recently attained outstanding speed-accuracy trade-offs, taking aside the memory requirements. In this paper, we revisit these approaches by considering, additionally, the memory constraint required to index billions of images on a single server.

By: Matthijs Douze, Alexandre Sablayrolles, Hervé Jégou
June 19, 2018

A Generative Adversarial Approach for Zero-Shot Learning from Noisy Texts

Computer Vision and Pattern Recognition (CVPR)

Most existing zero-shot learning methods consider the problem as a visual semantic embedding one. Given the demonstrated capability of Generative Adversarial Networks (GANs) to generate images, we instead leverage GANs to imagine unseen categories from text descriptions and hence recognize novel classes with no examples being seen.

By: Yizhe Zhu, Mohamed Elhoseiny, Bingchen Liu, Xi Peng, Ahmed Elgammal
June 18, 2018

Learning Patch Reconstructability for Accelerating Multi-View Stereo

Computer Vision and Pattern Recognition (CVPR)

We present an approach to accelerate multi-view stereo (MVS) by prioritizing computation on image patches that are likely to produce accurate 3D surface reconstructions. Our key insight is that the accuracy of the surface reconstruction from a given image patch can be predicted significantly faster than performing the actual stereo matching.

By: Alex Poms, Chenglei Wu, Shoou-I Yu, Yaser Sheikh
June 18, 2018

Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

Computer Vision and Pattern Recognition (CVPR)

Deep models that are both effective and explainable are desirable in many settings; prior explainable models have been unimodal, offering either image-based visualization of attention weights or text-based generation of post-hoc justifications. We propose a multimodal approach to explanation, and argue that the two modalities provide complementary explanatory strengths.

By: Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata, Anna Rohrbach, Bernt Schiele, Trevor Darrell, Marcus Rohrbach
June 18, 2018

Embodied Question Answering

Computer Vision and Pattern Recognition (CVPR)

We present a new AI task – Embodied Question Answering (EmbodiedQA) – where an agent is spawned at a random location in a 3D environment and asked a question (‘What color is the car?’). In order to answer, the agent must first intelligently navigate to explore the environment, gather necessary visual information through first-person (egocentric) vision, and then answer the question (‘orange’). 

By: Abhishek Das, Samyak Datta, Georgia Gkioxari, Stefan Lee, Devi Parikh, Dhruv Batra
June 18, 2018

A Holistic Framework for Addressing the World using Machine Learning

Computer Vision and Pattern Recognition (CVPR)

Millions of people are disconnected from basic services due to lack of adequate addressing. We propose an automatic generative algorithm to create street addresses from satellite imagery.

By: Ilke Demir, Forest Hughes, Aman Raj, Kaunil Dhruv, Suryanarayana Murthy Muddala, Sanyam Garg, Barrett Doo