#### About

Our workshop focuses on optimization theory and practice that is
relevant to machine learning. This proposal builds on precedent
established by two of our previously well-received NIPS
workshops:
*(@NIPS*08) http://opt2008.kyb.tuebingen.mpg.de/
*(@NIPS*09) http://opt.kyb.tuebingen.mpg.de/

Both these workshops had packed (often overpacked) attendance almost throughout the day. This enthusiastic reception reflects the strong interest, relevance, and importance enjoyed by optimization in the greater ML community. One could ask why does optimization attract such continued interest? The answer is simple but telling: optimization lies at the heart of almost every ML algorithm. For some algorithms textbook methods suffice, but the majority require tailoring algorithmic tools from optimization, which in turn depends on a deeper understanding of the ML requirements. In fact, ML applications and researchers are driving some of the most cuttingedge developments in optimization today. The intimate relation of optimization with ML is the key motivation for our workshop, which aims to foster discussion, discovery, and dissemination of the state-of-the-art in optimization, especially in the context of ML. The workshop should realize its aims by: *Providing a platform for increasing the interaction between researchers from optimization, operations research, statistics, scientific computing, and machine learning; *Identifying key problems and challenges that lie at the intersection of optimization and ML; *Narrowing the gap between optimization and ML, to help reduce rediscovery, and thereby accelerating new advances.

Workshop homepage: http://opt.kyb.tuebingen.mpg.de/

#### Related categories

## Uploaded videos:

## Invited Talks

### Limited-memory quasi-Newton and Hessianfree Newton methods for non-smooth optimi...

Jan 13, 2011

·

7909 Views

### Efficiency of Quasi-Newton Methods on Strictly Positive Functions

Jan 13, 2011

·

4698 Views

## Lectures

### Information-theoretic lower bounds on the oracle complexity of sparse convex opt...

Jan 13, 2011

·

4031 Views

### Hierarchical Classification via Orthogonal Transfer

Jan 13, 2011

·

3854 Views

### An Optimization Based Framework for Dynamic Batch Mode Active Learning

Jan 13, 2011

·

3550 Views

### Augmenting Dual Decomposition for MAP Inference

Jan 13, 2011

·

4131 Views

### An Incremental Subgradient Algorithm for Approximate MAP Estimation in Graphical...

Jan 13, 2011

·

3609 Views