Parallel Inference and Learning with Deep Structured Distributions
Many problems in real-world applications involve predicting several random variables which are statistically related. A structured model, like a Markov random field, is a great mathematical tool to encode those dependencies. Within the first part…
Fundamentals of P-Values: Introduction
TechFest Workshop – Theory Day – Session 5
The price of anarchy (PoA), which quantifies the degradation in the quality of outcomes in a (pure) Nash equilibrium of a game, is of fundamental importance in computational game theory. For many games, a pure…
Charles River Crypto Day: Delegating RAM Computations
In the setting of cloud computing a user wishes to delegate its data, as well as computations over this data, to a cloud provider. Each computation may read and modify the data, and these modifications…
Charles River Crypto Day: Constant-Round Interactive-Proofs for Delegating Computations
Interactive proofs have had a dramatic impact on Complexity Theory and Cryptography. In particular, the celebrated IP=PSPACE Theorem [LFKN92,Shamir92] allows an all-powerful but untrusted prover to convince a polynomial-time verifier of the validity of extremely…
Discovery of Latent Factors in High-dimensional Data via Tensor Decomposition
Latent or hidden variable models have applications in almost every domain, e.g., social network analysis, natural language processing, computer vision and computational biology. Training latent variable models is challenging due to non-convexity of the likelihood…
Guide to Applications of Homomorphic Encryption
Homomorphic encryption is an encryption function which permits encrypted data to be computed without decryption. It is considered as a solution for protecting privacy information in present situations such as cloud computing and machine communication.…