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A weekly series of seminars featuring experts in high-performance computing modeling, simulation and numerical computing, bioinformatics and computational biology, and large-scale data analysis and visualization.

### Recent Submissions

• #### The Aha! Moment: From Data to Insight ﻿

(Georgia Institute of Technology, 2014-02-07)
The amount of data in the world is increasing at incredible rates. Large-scale data has potential to transform almost every aspect of our world, from science to business; for this potential to be realized, we must turn ...
• #### Cyber Games ﻿

(Georgia Institute of Technology, 2013-02-19)
Over the last few years I have been working on game theoretic models of security, with a particular emphasis on issues salient in cyber security. In this talk I will give an overview of some of this work. I will first spend ...
• #### Magnetic Resonance Imaging of the Brain ﻿

(Georgia Institute of Technology, 2012-10-12)
Magnetic Resonance Imaging (MRI) has become a powerful, indispensable, and ubiquitously used methodology in neuroimaging. In particularly, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) ...
• #### Extending Hadoop to Support Binary-Input Applications ﻿

(Georgia Institute of Technology, 2012-10-19)
Many data-intensive applications naturally take multiple inputs, which is not well supported by some popular MapReduce implementations, such as Hadoop. In this talk, we present an extension of Hadoop to better support such ...
• #### Stochastic Gradient Descent with Only One Projection ﻿

(Georgia Institute of Technology, 2012-09-28)
Although many variants of stochastic gradient descent have been proposed for large-scale convex optimization, most of them require projecting the solution at {\it each} iteration to ensure that the obtained solution stays ...
• #### High-performance-computing challenges for heart simulations ﻿

(Georgia Institute of Technology, 2012-08-31)
The heart is an electro-mechanical system in which, under normal conditions, electrical waves propagate in a coordinated manner to initiate an efficient contraction. In pathologic states, propagation can destabilize and ...
• #### How much (execution) time and energy does my algorithm cost? ﻿

(Georgia Institute of Technology, 2012-08-24)
When designing an algorithm or performance-tuning code, is time-efficiency (e.g., operations per second) the same as energy-efficiency (e.g., operations per Joule)? Why or why not? To answer these questions, we posit a ...
• #### Graphical Models for the Internet ﻿

(Georgia Institute of Technology, 2011-04-29)
In this talk I will present algorithms for performing large scale inference using Latent Dirichlet Allocation and a novel Cluster-Topic model to estimate user preferences and to group stories into coherent, topically ...
• #### Optimization for Machine Learning: SMO-MKL and Smoothing Strategies ﻿

(Georgia Institute of Technology, 2011-04-15)
Our objective is to train $p$-norm Multiple Kernel Learning (MKL) and, more generally, linear MKL regularised by the Bregman divergence, using the Sequential Minimal Optimization (SMO) algorithm. The SMO algorithm is simple, ...
• #### Spatial Stochastic Simulation of Polarization in Yeast Mating ﻿

(Georgia Institute of Technology, 2011-04-19)
In microscopic systems formed by living cells, the small numbers of some reactant molecules can result in dynamical behavior that is discrete and stochastic rather than continuous and deterministic. Spatio-temporal gradients ...
• #### Coordinate Sampling for Sublinear Optimization and Nearest Neighbor Search ﻿

(Georgia Institute of Technology, 2011-04-22)
I will describe randomized approximation algorithms for some classical problems of machine learning, where the algorithms have provable bounds that hold with high probability. Some of our algorithms are sublinear, that is, ...
• #### Mining Billion-Node Graphs: Patterns, Generators, and Tools ﻿

(Georgia Institute of Technology, 2011-04-08)
What do graphs look like? How do they evolve over time? How to handle a graph with a billion nodes? We present a comprehensive list of static and temporal laws, and some recent observations on real graphs (like, e.g., ...
• #### Multicore-oblivious Algorithms ﻿

(Georgia Institute of Technology, 2011-03-28)
Multicores represent a paradigm shift in general-purpose computing away from the von Neumann model to a collection of cores on a chip communicating through a cache hierarchy under a shared memory. Designing efficient ...
• #### Modeling Rich Structured Data via Kernel Distribution Embeddings ﻿

(Georgia Institute of Technology, 2011-03-25)
Real world applications often produce a large volume of highly uncertain and complex data. Many of them have rich microscopic structures where each variable can take values on manifolds (e.g., camera rotations), combinatorial ...
• #### PHAST: Hardware-Accelerated Shortest Path Trees ﻿

(Georgia Institute of Technology, 2011-02-25)
We present a novel algorithm to solve the nonnegative single-source shortest path problem on road networks and other graphs with low highway dimension. After a quick preprocessing phase, we can compute all distances from ...
• #### The Exascale: Why and How ﻿

(Georgia Institute of Technology, 2011-02-11)
Sustained floating-point computation rates on real applications, as tracked by the ACM Gordon Bell Prize, increased by three orders of magnitude from 1988 (1 Gigaflop/s) to 1998 (1 Teraflop/s), and by another three orders ...
• #### New Approaches to Protein Functional Inference and Ligand Screening: Application to the Human Kinome ﻿

(Georgia Institute of Technology, 2011-01-14)
• #### Sequences of Problems, Matrices, and Solutions ﻿

(Georgia Institute of Technology, 2010-11-12)
In a wide range of applications, we deal with long sequences of slowly changing matrices or large collections of related matrices and corresponding linear algebra problems. Such applications range from the optimal design ...
• #### Metanumerical computing for partial differential equations: the Sundance project ﻿

(Georgia Institute of Technology, 2010-10-29)
Metanumerical computing deals with computer programs that use abstract mathematical structure to manipulate, generate, and/or optimize compute-intensive numerical codes. This idea has gained popularity over the last decade ...
• #### Gravity's Strongest Grip: A Computational Challenge ﻿

(Georgia Institute of Technology, 2010-10-22)
Gravitational physics is entering a new era driven by observation that will begin once gravitational-wave interferometers make their first detections. In the universe, gravitational waves are produced during violent events ...