The weekly SILO Seminar Series is made possible through the generous support of the 3M Company and its Advanced Technology Group

with additional support from the Analytics Group of the Northwestern Mutual Life Insurance Company

__Hongbo Dong | Sid Barman__, *Post-doc in WID and graduate student in CS*

** Date and Time: **Feb 08, 2012 (12:30 PM)

**Location: **
Orchard room (3280) at the Wisconsin Institute for Discovery Building

*** Hongbo's talk:

Title: Using a New Nonconvex Singular Value Regularizer in Multivariate Linear Regression.

Abstract:

We introduce the weighted singlar value penalization, which uses a nonconvex nonseparable

regularizer. We show that in spite of the nonconvexity, one optimization problem with this regularizer is efficiently solvable. Applied to Multivariate Linear Regression, we develop a new estimator for simultaneous dimension reduction and coefficient estimation. We prove the rank consistency and establish prediction and estimation performance bounds for our estimator. Advantages of our estimator are demonstrated by extensive simulation studies and an application in genetics. I will also discuss a variant of our optimization result that is applicable to sparse optimization.

*** Sid's talk

Title: Traffic-Redundancy Aware Network Design

Abstract:

We consider network design problems for information networks where routers can replicate data but

cannot alter it. This functionality allows the network to eliminate data-redundancy in traffic, thereby

saving on routing costs. We consider two problems within this framework and design approximation

algorithms.

The first problem we study is the traffic-redundancy aware network design (RAND) problem. We

are given a weighted graph over a single server and many clients. The server owns a number of different

data packets and each client desires a subset of the packets; the client demand sets form a laminar set

system. Our goal is to connect every client to the source via a single path, such that the collective cost

of the resulting network is minimized. Here the transportation cost over an edge is its weight times

times the number of distinct packets that it carries.

The second problem is a facility location problem that we call RAFL. Here the goal is to find an

assignment from clients to facilities such that the total cost of routing packets from the facilities to

clients (along unshared paths), plus the total cost of producing one copy of each desired packet at

each facility is minimized.

We present a constant factor approximation for the RAFL and an O(log P) approximation for

RAND, where P is the total number of distinct packets. We remark that P is always at most the

number of different demand sets desired or the number of clients, and is generally much smaller.

This is joint work with Shuchi Chawla.