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Feb 24 2013 - CVPR2012

My foray into image segmentation (SCALPEL) will be published at the upcoming CVPR conference in June.

June 17 2012 - CVPR2012

I am presenting work at the Workshop on Gesture Recogntion, where we achieved 2nd place in the CHALEARN One-shot Learning Challenge.

Feb 21 2011 - CVPR2011

I am co-author on a paper that was accepted for oral presentation at CVPR2011.

Aug 20 2010 - NIPS2010

I am co-organizing the NIPS 2010 workshop on Coarse-to-Fine Learning and Inference.

July 28 2009 - NY Times!

Dinosaur Planet is in the New York Times!

July 26, 2009 - Netflix!!

Along with the rest of The Ensemble, I finished in first place on the Netflix Prize Leaderboard at the end of the competition! We may or may not have won the prize, but it is a major accomplishment and a strong argument for the benefits of open collaboration. See my Netflix page for more.

February 6, 2009 - Update

I finally updated the website with a slightly tweaked design, better fonts and up-to-date content.

about me

I am a fifth-year graduate student in the Computer and Information Science (CIS) Department at the University of Pennsylvania. I am co-advised by Ben Taskar and Michael Kearns.

I do research in machine learning and specialize in computer vision and natural language processing. My research focuses on enabling more complex models via efficient, practical learning and inference procedures. I co-organized the NIPS 2010 workshop on Coarse-to-Fine Learning and Inference. I still enjoy neuroscience (as is my background); ultimately, I hope to promote the integration of machine learning and neuroscience, and to change the way we analyze and understand our minds.

I am currently a member of the GRASP Lab and the Penn Research in Machine Learning (PRIML) research groups. Previously, I was a research specialist at the Princeton Computational Memory Lab. I graduated from Princeton University with a degree in Computer Science and a certificate in Neuroscience in 2007, advised by Dave Blei (CS) and Ken Norman (Psychology).

In my spare time, I enjoy partaking in machine learning competitions. Most recently, I won 2nd place in the CHALEARN Gesture Challenge as part of Team Pennect. Before that, I was a member of Team Dinosaur Planet, Grand Prize Team, and The Ensemble, the greatest Netflix Prize wrecking crew ever created.

Finally, I'm also a founding software developer of MedForward Inc. and maintain several software packages of my own. I also contributed significantly to the MVPA Toolbox for Matlab.

highlighted projects

  • Structured Prediction Cascades. A general method for speeding up inference and enabling more complex models. This has led to state-of-the-art results in OCR, human pose estimation and tracking, and natural language parsing (extension by others). Code for linear-chain models is available here, human pose estimation in still images here, and in video here. Read about it in detail here.
  • Object segmentation with SCALPEL. A state-of-the-art image object segmentation algorithm that generates hundreds of object segmentation proposals per image with high recall. It uses refinement of localized shape priors with a cascade of greedy superpixel selectors. Read about it here and download code here.
  • One-shot gesture recognition. We used an HMM-based approach to win second place in the CHALEARN One-shot Learning Challenge. Learn more from my slides (with videos) in keynote or quicktime format.
  • Teaching Machine Learning and AI. I have worked with Professor Taskar for the past four years to advance the Penn Machine Learning cirriculum. This includes building an automated Matlab based homework submission and grading system, a live-updated Matlab based ML competition leaderboard, and even online educational videos, like the one below: Additionally, I designed and co-taught a novel undergraduate course using the 2011 Google AI Challenge as a motivating basis. As part of this I developed a user-friendly Python framework for students to use to complete assignments.
  • Enhanced Matlab toolboxes. In my own work and collaborations with Ben Sapp I've maintained two useful Matlab toolboxes: one for managing distributed experiments and another filled with generally useful functions. See my code page for more information.

publications

  • PDF
    Code     SCALPEL: Segmentation CAscasdes with Localized Priors and Efficient Learning.
    David Weiss and Ben Taskar.
    Computer Vision and Pattern Recognition (CVPR), June 2013.
  • PDF Structured Prediction Cascades.
    David Weiss, Benjamin Sapp, and Ben Taskar.
    Pre-print; under review at JMLR.
  • PDF
    Slides
    Code     Parsing Human Motion with Stretchable Models.
    Benjamin Sapp, David Weiss, and Ben Taskar.
    Computer Vision and Pattern Recognition (CVPR), June 2011.
    (Oral presentation, 3.5% acceptance)
  • PDF | Supp. Info
    Poster
    Code     Sidestepping Intractable Inference with Structured Ensemble Cascades.
    David Weiss, Benjamin Sapp, and Ben Taskar.
    Neural Information Processing Systems (NIPS), December 2010.
  • PDF | Supp. Info
    Code     Mixed Membership Matrix Factorization.
    Lester Mackey, David Weiss, and Michael I. Jordan.
    International Conference on Machine Learning (ICML), June 2010.
  • PDF
    Poster
    Code     Structured Prediction Cascades.
    David Weiss and Ben Taskar.
    International Conference on Artificial Intelligence and Statistics (AISTATS), May 2010.
  • URL Listening for recollection: A multi-voxel pattern analysis of recognition memory retrieval strategies.
    Joel R. Quamme, David J. Weiss, and Kenneth A. Norman.
    Frontiers in Human Neuroscience, 4(0), 2010.
  • PDF Probabilistic Additive Component Analysis: A Latent Variable Model for Dimensionality Reduction of Human fMRI Datasets.
    David Weiss. Senior Thesis, Princeton University, May 2007.
  • PDF Haptic Rendering of Tissue Cutting with Scissors in a Virtual Environment.
    David Weiss and Alison Okamura.
    Medicine Meets Virtual Reality 12, J.D. Westwood, et al. (Eds.), IOS Press, 2004, pp. 407-409.