Publications

Journals

• H. Shen, S. Jegelka and A. Gretton. Fast Kernel-based Independent Component Analysis. IEEE Transactions on Signal Processing 57(9), pp. 3498-3511, 2009.
• S. Jegelka, J. A. Bednar and R. Miikkulainen. Prenatal Development of Ocular Dominance in a Self-organizing Model of V1. Neurocomputing 69, pp. 1291-1296, 2006.

Conferences and Book Chapters

• R. Iyer, S. Jegelka and J. Bilmes. Fast Semidifferential-based Submodular Function Optimization. International Conference on Machine Learning (ICML), 2013. (supplement)
• P. Kohli, A. Osokin and S. Jegelka. A principled deep random field for image segmentation. IEEE Conference of Computer Vision and Pattern Recognition (CVPR), 2013 (supplement)
• S. Jegelka, H. Lin and J. Bilmes. On Fast Approximate Submodular Minimization. 25th Annual Conference on Neural Information Processing Systems (NIPS), 2011.
• S. Jegelka and J. Bilmes. Online Submodular Minimization for Combinatorial Structures. 28th International Conference on Machine Learning (ICML), 2011. (Supplementary material)
• S. Jegelka and J. Bilmes. Approximation Bounds for Inference using Cooperative Cut. 28th International Conference on Machine Learning (ICML), 2011.
• S. Jegelka and J. Bilmes. Submodularity beyond Submodular Energies: Coupling Edges in Graph Cuts. IEEE Conference of Computer Vision and Pattern Recognition (CVPR), 2011 (oral presentation, 3.5% acceptance rate). (Supplementary material)
• S. Jegelka, S. Sra and A. Banerjee. Approximation Algorithms for Tensor Clustering. Algorithmic Learning Theory: 20th International Conference (ALT), 2009.
• S. Nowozin and S. Jegelka. Solution Stability in Linear Programming Relaxations: Graph Partitioning and Unsupervised Learning. 26th International Conference on Machine Learning (ICML), 2009.
• S. Jegelka, A. Gretton, B. Schoelkopf, B.K. Sriperumbudur and U. von Luxburg. Generalized Clustering via Kernel Embeddings. KI 2009: Advances in Artificial Intelligence, 2009.
• U. von Luxburg, S. Bubeck, S. Jegelka and M. Kaufmann. Consistent Minimization of Clustering Objective Functions. 21st Annual Conference on Neural Information Processing Systems (NIPS), 2007.
• H. Shen, S. Jegelka and A. Gretton. Fast Kernel ICA using an Approximate Newton Method. 11th Conference on Artificial Intelligence and Statistics (AISTATS), 2007.
• S. Jegelka and A. Gretton. Brisk Kernel Independent Component Analysis. In L. Bottou, O. Chapelle, D. DeCoste, J. Weston, editors. Large Scale Kernel Machines, pp. 225-250. MIT Press, 2007.

Abstracts and Contributions to Workshops

• R. Iyer, S. Jegelka and J. Bilmes. Mirror Descent-Like Algorithms for Submodular Optimization. NIPS 2012 Workshop on Discrete Optimization in Machine Learning.
• S. Jegelka and J. Bilmes. Multi-label Cooperative Cuts. CVPR 2011 Workshop on Inference in Graphical Models with Structured Potentials.
• S. Jegelka and J. Bilmes. Coupling Edges in Graph Cuts. SIAM Conference on Optimization, 2011.
• S. Jegelka and J. Bilmes. Online Algorithms for Submodular Minimization with Combinatorial Constraints. NIPS 2010 Workshop Discrete Optimization in Machine Learning.
• S. Jegelka and J. Bilmes. Cooperative Cuts: Graph Cuts with Submodular Edge Weights. EURO XXIV (24th European Conference on Operational Research), 2010.
• S. Jegelka and J. Bilmes. Notes on Graph Cuts with Submodular Edge Weights. NIPS 2009 Workshop Discrete Optimization in Machine Learning.
• S. Jegelka, A. Gretton and D. Achlioptas. Kernel ICA for Large Scale Problems. NIPS 2005 Workshop on Large Scale Kernel Machines.

Technical Reports

• S. Jegelka and J. Bilmes. Cooperative Cuts for Image Segmentation, UWEETR-1020-0003, University of Washington, 2010.
• S. Jegelka and J. Bilmes. Cooperative Cuts: Graph Cuts with Submodular Edge Weights. MPI-TR 189, 2010.
• S. Sra, S. Jegelka and A. Banerjee. Approximation Algorithms for Bregman Clustering, Co-Clustering and Tensor Clustering. MPI-TR 177, 2008.
• B. Kulis, S. Sra and S. Jegelka. Scalable Semidefinite Programming using Convex Perturbations. TR 07-47, University of Texas at Austin, 2007.
• H. Shen, S. Jegelka and A. Gretton. Geometric Analysis of Hilbert Schmidt Independence Criterion based ICA contrast function. TR PA006080, NICTA, 2006.

Theses

• Combinatorial Problems with Submodular Coupling in Machine Learning and Computer Vision. Ph.D. Thesis, ETH Zurich, 2012.
• Statistical Learning Theory Approaches to Clustering. Diplom Thesis, 2007.