Microsoft Research

1. 'Unconference Session Report Back: The Need for and Strategy for Building Shared Resources for Bot Developers' by Ben Brown, Howdy.ai, 0:01 2.

Microsoft Research – 8 июля 2016, 21:21

Microsoft Research – 8 июля 2016, 20:41

"Long-Range Planning with Time-Inconsistency: A Class of Computational Problems in Behavioral Economics There are many settings where people set long-range goals and make plans to achieve them.

Preference reasoning and aggregation are the main ingredients of a very active area of research which brings together multi-agent systems, knowledge representation, combinatorial optimisation, and

October 5: Modeling Day 9:30am-10:30am Model Based Machine Learning 1: A Gentle Introduction Chris Bishop In the traditional approach to problem solving with machine learning, the developer

Entity relationship search at the Web scale or even at the Enterprise level depends on adding dozens of entity annotations to each of billions of crawled pages and indexing the annotations at rates

I will describe plausible lattice-based constructions with properties that approximate the sought-after multilinear maps in hard-discrete-logarithm groups.

Title: A Crash Course on Model Checking Date: Three Sessions: 10/28/99, 11/4/99, 11/11/99 Description: In recent years, model checking has been widely successful in finding bugs in hardware design

This talk is in three parts. The first deals with an aspect of the Weka project that has received little attention, namely the use of machine learning in agricultural applications.

Recent work has solidly established lattice-based signatures as a viable replacement for number-theoretic schemes should quantum computing come into fruition.

S V N Vishwanathan (Vishy) and Prateek Jain will offer a 10 week Machine Learning course. It will be an exciting mix between theory and application talks by various guest lecturers.

Microsoft Research – 8 июля 2016, 1:03

Coppersmith's technique using lattices to find small roots of polynomial equations (and Howgrave-Graham's extension to solving equations modulo divisors) have produced many fascinating results

Social Computing Symposium 2016: Post Screen Personas and Listening Machines, Apparent Agency & Invisible Agendas Software agents and social robots are designed so that we imbue them with

Chair: Hernan Chaimovich, Brazilian Academy of Sciences Speakers: Marina Hirota, Federal University of Santa Catarina Agma Traina, University of São Paulo at São Carlos Rosiane de Freitas, Federal

Microsoft Research – 8 июля 2016, 1:00

In this talk I will survey a recently introduced cryptographic problem called Learning with Rounding (LWR).

ML Day 2014 - "Perceptual Annotation": from Biologically Inspired, to Biologically Informed Machine Learning Many machine learning applications, explicitly or implicitly, attempt to mimic natural

CTR (Click Through Rate) prediction is extremely important for Internet advertisements. Data of users' impression and click logs possess two major challenges.

Social Computing Symposium 2016: Harassment, Threats, and Trolling Online, Architectural Intelligence in the Age Of Social Computing

The best generic tool currently known for attacking lattice-based cryptographic primitives is lattice reduction.

Data is being generated at a tremendous rate in modern applications as diverse as internet applications, genomics, health care, energy management and social network analysis.

October 1: Beginning Day 9:30am-10:45am Intro to Machine Learning: Part I John Langford and Vijay Narayanan I’ll discuss what machine learning is at a high level and provide a short overview of the

This talk asks the question of how we can intervene, in a predictive manner, in complex multi-cellular, multi-cytokine/chemokine, multi-pathway system.

Isaac (Zak) Kohane Embracing noise and heterogeneity In clinical medicine, the gold standard for evidence is the randomized controlled trial.

Copy-number alterations are among the most common alterations in cancer, and affect more of the genome than any other alteration.

Microsoft Research – 8 июля 2016, 0:49

Approximate Bayesian computation (ABC) algorithms are a class of Monte Carlo methods for doing inference when the likelihood function can be simulated from, but not explicitly evaluated.

Achieving the Full Potential of State Machine Replication: High Throughput, Low Latency, Constant Availability Redundancy through state replication is the primary mechanism for achieving fault