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558 Results

October 24, 2014

The HipHop Virtual Machine

ACM International Conference on Object Oriented Programming Systems, Languages, and Applications

The HipHop Virtual Machine (HHVM) is a JIT compiler and runtime for PHP. While PHP values are dynamically typed, real programs often have latent types that are useful for optimization once discovered….

By: Keith Adams, Jason Evans, Bertrand Maher, Guilherme Ottoni, Drew Paroski, Brett Simmers, Edwin Smith, Owen Yamauchi
October 7, 2014

f4: Facebook’s Warm BLOB Storage System

Operating Systems Design and Implementation

Facebook’s corpus of photos, videos, and other Binary Large OBjects (BLOBs) that need to be reliably stored and quickly accessible is massive and continues to grow.

By: Subramanian Muralidhar, Wyatt Lloyd, Sabyasachi Roy, Cory Hill, Ernest Lin, Weiwen Liu, Satadru Pan, Shiva Shankar, Viswanath Sivakumar, Linpeng Tang, Sanjeev Kumar
October 6, 2014

The Mystery Machine: End-to-end Performance Analysis of Large-scale Internet Services

Operating Systems Design and Implementation

Current debugging and optimization methods scale poorly to deal with the complexity of modern Internet services, in which a single request triggers parallel execution of numerous heterogeneous softwar…

By: Mike Chow, David Meisner, Jason Flinn, Daniel Peek, Thomas Wenisch
September 18, 2014

Hierarchical Cascade of Classifiers for Efficient Poselet Evaluation

British Machine Vision Conference

Poselets have been used in a variety of computer vision tasks, such as detection, segmentation, action classification, pose estimation and action recognition, often achieving state-of-the-art performa…

By: David Bo Chen, Pietro Perona, Lubomir Bourdev
September 18, 2014

Mining Energy Traces to Aid in Software Development: An Empirical Case Study

ACM / IEEE International Symposium on Empirical Software Engineering and Measurement

With the advent of increased computing on mobile devices such as phones and tablets, it has become crucial to pay attention to the energy consumption of mobile applications.

By: Ashish Gupta, Thomas Zimmermann, Christian Bird, Nachiappan Nagappan, Thirumalesh Bhat, Syed Emran
September 4, 2014

Question Answering with Subgraph Embeddings

Empirical Methods in Natural Language Processing

This paper presents a system which learns to answer questions on a broad range of topics from a knowledge base using few handcrafted features. Our model learns low-dimensional embeddings of words and knowledge base constituents; these representations are used to score natural language questions against candidate answers.

By: Antoine Bordes, Jason Weston, Sumit Chopra
September 4, 2014

#TagSpace: Semantic Embeddings from Hashtags

Empirical Methods in Natural Language Processing

We describe a convolutional neural network that learns feature representations for short textual posts using hashtags as a supervised signal. The proposed approach is trained on up to 5.5 billion words predicting 100,000 possible hashtags.

By: Jason Weston, Sumit Chopra, Keith Adams
September 1, 2014

Optimal Crowd-Powered Rating and Filtering Algorithms

VLDB 2014

We focus on crowd-powered filtering, i.e., filtering a large set of items using humans. Filtering is one of the most commonly used building blocks in crowdsourcing applications and systems. While solu…

By: Aditya Parameswaran, Stephen Boyd, Hector Garcia-Molina, Ashish Gupta, Neoklis Polyzotis, Jennifer Widom
August 24, 2014

Streamed Approximate Counting of Distinct Elements

ACM Conference on Knowledge Discovery and Data Mining (KDD)

Counting the number of distinct elements in a large dataset is a common task in web applications and databases. This problem is difficult in limited memory settings where storing a large hash table ta…

By: Daniel Ting
August 24, 2014

Practical Lessons from Predicting Clicks on Ads at Facebook

International Workshop on Data Mining for Online Advertising (ADKDD)

Online advertising allows advertisers to only bid and pay for measurable user responses, such as clicks on ads. As a consequence, click prediction systems are central to most online advertising system…

By: Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu, Tao Xu, Yanxin Shi, Antoine Atallah, Stuart Bowers, Joaquin QuiƱonero Candela