From awd at cs.cmu.edu Sun Aug 2 20:26:10 2015 From: awd at cs.cmu.edu (Artur Dubrawski) Date: Sun, 2 Aug 2015 20:26:10 -0400 Subject: Fwd: Reminder - Thesis Defense - 8/3/15 - Ina Fiterau - Discovering Compact and Informative Structures through Data Partitioning In-Reply-To: <55BE741B.2070302@cs.cmu.edu> References: <55BE741B.2070302@cs.cmu.edu> Message-ID: <55BEB522.5010003@cs.cmu.edu> Dear Autonians, If you are available please come and cheer Ina on her path to completion. Her thesis defense will take place this Monday at 10am in Gates Hall room 6115. See you there! Artur -------- Forwarded Message -------- Subject: Reminder - Thesis Defense - 8/3/15 - Ina Fiterau - Discovering Compact and Informative Structures through Data Partitioning Date: Sun, 02 Aug 2015 15:48:43 -0400 From: Diane Stidle To: ML-SEMINAR at cs.cmu.edu, Andreas Krause Thesis Defense Date: 8/3/15 Time: 10:00am Place: 6115 GHC PhD Candidate: Madalina Fiterau-Brostean Title: Discovering Compact and Informative Structures through Data Partitioning Abstract: In this thesis, we have shown that it is possible to identify low-dimensional structures in complex high-dimensional data, if such structures exist. We have leveraged these underlying structures to construct compact interpretable models for various machine learning tasks that benefit practical applications. To start with, I will formalize Informative Projection Recovery, the problem of extracting a small set of low-dimensional projections of data that jointly support an accurate model for a given learning task. Our solution to this problem is a regression-based algorithm that identifies informative projections by optimizing over a matrix of point-wise loss estimators. It generalizes to multiple types of machine learning problems, offering solutions to classification, clustering, regression, and active learning tasks. Experiments show that our method can discover and leverage low-dimensional structures in data, yielding accurate and compact models. Our method is particularly useful in applications in which expert assessment of the results is of the essence, such as classification tasks in the healthcare domain. In the second part of the talk, I will describe back-propagation forests, a new type of ensemble that achieves improved accuracy over existing ensemble classifiers such as random forests classifiers or alternating decision forests. Back-propagation (BP) trees use soft splits, such that a sample is probabilistically assigned to all the leaves. Also, the leaves assign a distribution across the labels. The splitting parameters are obtained through SGD by optimizing the log loss over the entire tree, which is a non-convex objective. The probability distribution over the leaves is computed exactly by maximizing a log concave procedure. In addition, I will present several proposed approaches for the use of BP forests within the context of compact informative structure discovery. We have successfully used BP forests to increase the performance of deep belief network architectures, with results improving over the state of the art on vision datasets. Thesis Committee: Artur Dubrawski, Chair Geoff Gordon Alex Smola Andreas Krause (ETH Zurich) -- Diane Stidle Graduate Programs Manager Machine Learning Department Carnegie Mellon University diane at cs.cmu.edu 412-268-1299 -------------- next part -------------- An HTML attachment was scrubbed... URL: From awd at cs.cmu.edu Mon Aug 10 22:20:18 2015 From: awd at cs.cmu.edu (Artur Dubrawski) Date: Mon, 10 Aug 2015 22:20:18 -0400 Subject: labeling data for Chao Message-ID: <55C95BE2.7060600@cs.cmu.edu> Team, Recently, some of us had a chance to see Chao present his work on the capillary blood flow video analysis. This is a very promising work that currently hinges on having a sufficient supply of labeled training data. Chao has developed a GUI that can be used to make labeling quite straightforward. He is looking for volunteers to actually do the work. I am willing to invest the Lab's money and buy good quality candy as handouts for those who'd contribute to the effort. Please communicate with Chao directly (chaoliu1 at cs.cmu.edu) for instructions if you'd like and have capacity to help. Thanks! Artur From awd at cs.cmu.edu Wed Aug 19 14:06:36 2015 From: awd at cs.cmu.edu (Artur Dubrawski) Date: Wed, 19 Aug 2015 14:06:36 -0400 Subject: Auton Lab guest lecture by Dr. Michael Pinsky (Pitt/UPMC): Wednesday August 26th, 3-5pm, GHC 4405 Message-ID: <55D4C5AC.5080108@cs.cmu.edu> Dear Autonians, Please come and join us in hearing a lecture by one of our best friends and strongest collaborators. Title: Human cardiovascular physiology for dummies. Speaker: Michael R. Pinsky, MD, CM, Dr hc, MCCM, FCCP Professor of Critical Care Medicine, Bioengineering, Cardiovascular Disease and Anesthesiology Department of Critical Care Medicine University of Pittsburgh School of Medicine Cookies and coffee/tea will be provided. Note the unusual place: Gates-Hillman Center 4405. Cheers, Artur From awd at cs.cmu.edu Wed Aug 26 14:17:17 2015 From: awd at cs.cmu.edu (Artur Dubrawski) Date: Wed, 26 Aug 2015 14:17:17 -0400 Subject: CANCELED [Auton Lab guest lecture by Dr. Michael Pinsky (Pitt/UPMC): Wednesday August 26th, 3-5pm, GHC 4405] In-Reply-To: <55D4C5AC.5080108@cs.cmu.edu> References: <55D4C5AC.5080108@cs.cmu.edu> Message-ID: <55DE02AD.4080202@cs.cmu.edu> Team, I've just learned that regrettably Dr. Pinsky will not be able to make it to the meeting today. We will reschedule his presentation for a later date to be determined. Apologies for the lat notice. Cheers Artur On 8/19/2015 2:06 PM, Artur Dubrawski wrote: > Dear Autonians, > > Please come and join us in hearing a lecture by one of our best > friends and strongest collaborators. > > Title: Human cardiovascular physiology for dummies. > > Speaker: Michael R. Pinsky, MD, CM, Dr hc, MCCM, FCCP > Professor of Critical Care Medicine, Bioengineering, Cardiovascular > Disease and Anesthesiology > Department of Critical Care Medicine > University of Pittsburgh School of Medicine > > Cookies and coffee/tea will be provided. > > Note the unusual place: Gates-Hillman Center 4405. > > Cheers, > Artur