Random Features for very large scale machine learning.
Real-time Visual Object Instance Recognition.
Unsupervised and Semisupervised learning for tracking.
Localization and calibration of sensor networks deployed for tracking.
Visual 3D tracking without drift using view-based appearance models.
Random Kitchen Sinks: Replacing Optimization with
Randomization in Learning,
Ali Rahimi, Ben Recht,
in Neural Information Processing Systems (NIPS) 2008.
(to appear)
Uniform Approximation of Functions with Random Bases,
Ali Rahimi, Ben Recht,
in Allerton 2008.
(pdf)
Random Features for Large-Scale Kernel Machines,
Ali Rahimi, Ben Recht,
in Neural Information Processing Systems (NIPS) 2007.
(pdf)
The Mobile Sensing Platform: An Embedded Activity Recognition System, T. Choudhury,
G. Borriello, S. Consolvo, D. Haehnel, B. Harrison, B. Hemingway, J. Hightower, P. Klasnja, K. Koscher, A. LaMarca, J. A. Landay, L. LeGrand, J. Lester, A. Rahimi, A. Rea, D. Wyatt,
in IEEE Pervasive Computing, vol. 7, no. 2, jun 2008, pp. 32-41
Learning to Transform Time Series with a Few Examples,
Ali Rahimi, Ben Recht,
in Pattern Analysis and Machine Intelligence (PAMI)
vol. 29, no. 10, pp. 1759-1775, Oct., 2007
(pdf)
Estimating Observation Functions in Dynamical Systems using
Unsupervised Regression,
Ali Rahimi, Ben Recht,
in Neural Information Processing Systems (NIPS) 2006.
(pdf,,poster,slides)
Simultaneous Localization, Calibration, and Tracking in an ad Hoc Sensor
Network, C. Taylor, A. Rahimi, J. Bachrach, and H. Shrobe,
in Information Processing in Sensor Networks (IPSN) 2006.
(pdf,Powerpoint presentation)
Reducing Drift in Differential Tracking,
Ali Rahimi, Louis-Philippe Morency, Trevor Darrell,
in Computer Vision and Image Understanding (CVIU) 2006.
(pdf)
Learning to transform time Series with a Few Examples,
Ali Rahimi,
PhD thesis, Massachusetts Insitute of Technology, 2005.
(pdf)
Learning Appearance Manifolds from Video,
Ali Rahimi, Ben Recht,
in Computer Vision and Pattern Recognition (CVPR) 2005.
(pdf)
[see the full journal version]
Clustering with Normalized Cuts is Clustering with a Hyperplane,
Ali Rahimi, Ben Recht,
in Statistical Learning in Computer Vision 2004.
(pdf)
Simultaneous Calibration and Tracking with a Network
of Non-Overlapping Sensors,
Ali Rahimi, Brian Dunagan, Trevor Darrell,
in Computer Vision and Pattern Recognition (CVPR) 2004.
(pdf).
A techreport version (pdf).
A version with a non-convergence proof for the simpler case (pdf).
Tracking People with a Sparse Network of Bearing Sensors,
Ali Rahimi, Brian Dunagan, Trevor Darrell,
in European Conference on Computer Vision (ECCV) 2004.
(pdf)
Adaptive View-Based Appearance Models,
Louis-Philippe Morency, Ali Rahimi, Trevor Darrell,
in Computer Vision and Pattern Recognition (CVPR) 2003.
(pdf)
[see the full journal version]
Location Estimation with a Differential Update Network,
Ali Rahimi, Trevor Darrell,
in Neural Information Processing Systems (NIPS) 2002.
(pdf)
[see the full journal version]
Bayesian Network for Online Global Pose Estimation,
Ali Rahimi, Trevor Darrell, in
Proceedings of International Conference on Intelligent Robots and Systems (IROS), 2002.
(pdf)
Face-responsive interfaces: from direct manipulation to perceptive presence
, David Demirdjian, Konrad Tollmar, Frank Bentley, Neal Checka,
Louis-Philippe Morency, Ali Rahimi, Alice Oh, Trevor Darrell, in
UBICOMP, 2002.
Fast 3D Model Acquisition from Stereo Images,
Louis-Philippe Morency, Ali Rahimi, Trevor Darrell,
in 3D Data Processing, Visualization and Transmission (3DPVT), 2002.
(pdf)
Fast Stereo-Based Head Tracking for Interactive Environment,
Louis-Philippe Morency, Ali Rahimi, Neal Checka, Trevor Darrell,
in
Proceedings of the Int. Conference on Automatic Face and Gesture Recognition (F&G) 2002. (pdf)
Reducing Drift in Parametric Motion Tracking,
A. Rahimi, L-P. Morency, T. Darrell,
in International Conference on Computer Vision (ICCV) 2001. (pdf)
[see the full journal version]
Tracking Conversational Context for Machine Mediation of Human Discourse,
T. Jebara, Y. Ivanov, A. Rahimi, A. Pentland,
in AAAI Fall Symposium (2000).
Articulated-pose estimation using brightness-and depth-constancy constraints,
M. Covell, A. Rahimi, M. Harville, T. Darrell,
in Computer Vision and Pattern Recognition (CVPR), vol. 2, pp. 438-445, Jun 2000. (web page)
3D pose tracking with linear depth and brightness constraints,
M. Harville, A. Rahimi, T. Darrell, G. Gordon, J. Woodfill,
in International Conference on Computer Vision (ICCV), vol. 1, pp.206-213, 1999.
These are derivations I have found myself sharing with colleagues. You might find them useful. They lack citations and demonstrations with simulations or applications, so they are not complete.
The Solution of some Linear Projection and Reconstruction Problems Penalized by the Frobenius Norm (pdf). This table summarizes the result.
Bounding the Distance between MAP and ML Estimates (pdf).
The similarity between the logit loss and the SVM loss (pdf).
Outlier Rejection and M-Estimation with EM (pdf).
Minimum KL-Divergence simplification of a Factored Distribution (pdf).
