Stochastic Forecasts Achieve High Throughput and Low Delay over Cellular Networks Keith Winstein, Anirudh Sivaraman, and Hari Balakrishnan MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Mass. {ke

Source URL: www.usenix.org

CommunityFinder: Software to Analyze Communities that Develop in MOOC Discussion Forums Max Kanter Kalyan Veeramachaneni Any Scale Learning for All Computer Science and Artificial Intelligence Laboratory

Source URL: groups.csail.mit.edu

• Algebraic graph theory
• Community structure
• Spectral clustering
• Eigenvalues and eigenvectors
• Massive open online course
• Modularity
• Adjacency matrix
• Graph partition
• Book:Graph Theory I

Implications of a Data Structure Consistency Checking System Viktor Kuncak, Patrick Lam, Karen Zee, and Martin Rinard MIT Computer Science and Artificial Intelligence Laboratory 32 Vassar Street, Cambridge, MA 02139, USA

Source URL: patricklam.ca

Kalyan Veeramachaneni Computer Science and Artificial Intelligence Laboratory, 32-D540, MIT, Cambridge, MA 02139, USA, This version: January 8, 2016 Latest: www.kalyanv.org

Source URL: groups.csail.mit.edu

• Evolution
• Cybernetics
• Machine learning
• Association for Computing Machinery
• Genetic and Evolutionary Computation Conference
• Deep feature synthesis
• Evolutionary computation
• Data mining
• Evolutionary algorithm
• Computational intelligence
• Academia
• Computer science

Collecting Things Under Time Pressure is Hard Jayson Lynch MIT Computer Science and Artificial Intelligence Laboratory,

Source URL: tinytocs.ece.utexas.edu

Low Latency Geo-distributed Data Analytics – Public Review Mohammad Alizadeh MIT Computer Science and Artificial Intelligence Laboratory

Source URL: conferences.sigcomm.org

Greed is Good if Randomized: New Inference for Dependency Parsing Yuan Zhang∗, Tao Lei∗, Regina Barzilay, and Tommi Jaakkola Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technolo

Source URL: people.csail.mit.edu

Using Semantic Unification to Generate Regular Expressions from Natural Language Nate Kushman Regina Barzilay Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology {nkushman, regin

Source URL: people.csail.mit.edu

Risk and Regret of Hierarchical Bayesian Learners Jonathan H. Huggins Computer Science and Artificial Intelligence Laboratory, MIT arXiv:1505.04984v1 [cs.LG] 19 May 2015

Source URL: arxiv.org

Learning Visual Representations using Images with Captions Ariadna Quattoni Michael Collins Trevor Darrell MIT Computer Science and Artificial Intelligence Laboratory Cambridge MAariadna, mcollins, trevor @csail.m

Source URL: snowbird.djvuzone.org