Research Seminar "Machine Learning Theory"

This is the research seminar by Ulrike's group and everybody else who is interested

When and where

Each wednesday, 13:30 - 14:30 in the S2 Seminar room at the Max Planck Institute for Intelligent Systems (you need a card to enter the building; if you want to attend but you don't have one, please get in touch with somebody in our group, so we can let you in the building). Typically, we also meet for lunch at about 12:45 at the MPI cafeteria. (Note: the seminar is also listed in the university campus system, and there the date/time might be wrong.)


Most sessions take place in form of a reading group: everybody reads the assigned paper before the meeting. Then we are going to discuss the paper in the meeting. Sometimes we also have talks by guests or members of the group.


Everybody who is interested in machine learning theory. Students, PhD students and researchers alike. We do not mind people dropping in and out depending on whether they find the current session interesting or not.

Upcoming meetings

Suggested papers for future meetings

Past meetings

In Hamburg (2012-2015)

  • 4.6.2015 Paper discussion: Florent Krzakala, Cristopher Moore, Elchanan Mosseld, Joe Neemand, Allan Sly, Lenka Zdeborová, and Pan Zhanga: Spectral redemption in clustering sparse networks, PNAS 2013 pdf
  • 28.5.2015 Paper discussion: Wauthier, Jojic, Jordan: Active spectral clustering via iterative uncertainty reduction. KDD, 2012. link
  • 21.5.2015 Paper discussion: Jun Li , Juan A. Cuesta-Albertos, Regina Y. Liu, DD-Classifier: Nonparametric Classification Procedure Based on DD-Plot, JASA 2015. link
  • 27.4.2015: Talk by Ruth Urner, Max Planck Institute for Intelligent Systems, Tuebingen.
  • 23.4. 2015 Paper discussion: Learning Mixtures of Ranking Models (ranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan, NIPS 2014)
  • 16.4. 2015 Paper discussion: Almost no label to cry (Giorgio Patrini, Richard Nock, Tiberio Caetano, Paul Rivera, NIPS 2014)
  • 9.4. 2015 Paper discussion: Discrete Graph Hashing (Wei Liu, Cun Mu, Sanjiv Kumar, Shih-Fu Chang, NIPS 2014)
  • 26.2.2015 We discuss again the paper "Ranking and combining multiple predictors without labeled data" pdf. Focus is on understanding how the key lemma 1 can be true and why it makes sense. Everybody prepare seriously, please ...
  • 5.3. 2015 Machine learning brainstorming day!
    9-10 Tobias Lang: Active learning with user feedback
    10 - 11 Morteza Alamgir: Centrality based graph kernels
    11-12: Mehdi Sajjadi: peer grading algorithms, our data, our current insights
    12 - 13 lunch
    13 - 14 Sven Kurras: Clustering in an online game with adversarial players
    14 - 15 Rita Morisi: Spectral clustering applied to the Consensus problem
    Unfortunately, the talk by Matthaeus has to be skipped (was: Estimating median and modes and clusters from ordinal crowd data)
  • 19.2. Two Bachelor-thesis defense talks
    Jonas Häring: Comparing graphs with small doubling dimension to expander graphs
    Alexis Engelke: Streaming algorithms for graph partitioning
  • 12.2.2015 Paper discussion: Heikinheimo, Ukkonen. The crowd-median algorithm. First AAAI Conference on Human Computation and Crowdsourcing, 2013. pdf.
  • 5.2.2015 Talk by Rita Morisi (Institute of Advanced Studies Lucca, Italy): Graph based techniques in machine learning and control
  • 29.1. 2015 Paper discussion: Parisi, Nadler et al, PNAS 2014: Ranking and combining multiple predictors without labeled data pdf
  • 22.1. 2015 Talk by Thomas Buehler, Uni Saarbruecken: Titel: A flexible framework for solving constrained ratio problems in machine learning
  • 15.1.2015 Paper discussion: Distributed Balanced Clustering via Mapping Coresets, NIPS 2014 pdf
  • 8.1. 2015 Paper discussion: Scalable Simple Random Sampling and Stratified Sampling, ICML 2013 pdf
  • 18.12.2014 Paper discussion: Sinkhorn Distances: Lightspeed Computation of Optimal Transport. M. Cuturi, NIPS 2013 pdf
  • 11.12.2014 Paper discussion: Dimensionality Reduction with Subspace Structure Preservation, NIPS 2014 pdf
  • 4.12. 2014 Paper discussion: Graph clustering via a discrete uncoupling process. Stijn van Dongen. SIAM J. MATRIX ANAL. APPL. 2008 pdf
  • 27.11.2014 We discuss the following two papers, just high level:
    Fennel: Streaming graph partitioning for massive scale graphs. 2014 pdf
    Streaming graph partitioning for large distributed graphs. I Stanton, G Kliot, KDD 2012. pdf
  • 13.11.2014 Paper discussion: Network-based statistic: identifying differences in brain networks A Zalesky, A Fornito, ET Bullmore - Neuroimage, 2010. pdf
  • 20.11.2014 Talk by Maximilian Christ, University of Dortmund: SNP DNA analysis with logic regression.
  • 30.10.2014 Master defense talk by Longshan Sun: Algorithms for peer assessment.
  • 23.10.2014 Paper discussion: On the convergence of maximum variance unfolding Ery Arias-Castro, Bruno Pelletier. JMLR, 2013 pdf
  • 16.10.2014 Paper discussion: Ohad Shamir: Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation. Arxiv 2014. link (we read the main paper, don't dive into the proofs if you don't have time).
  • 2.10.2014 Talk by Tobias Lang, Zalando, Berlin (at 11:00!): From Planning and Exploration in Stochastic Relational Worlds to Recommender Systems in the E-Commerce World
  • 24.8.2014 Sundus Israr's Master defense test talk
  • 10.7. 2014 Morteza Alamgir's thesis defense test talk.
  • 3. 6. 2014 A whole day of talks!
    9:00 - 9:45 Matthaeus Kleindessner: Uniqueness of Ordinal Embedding
    9:45 - 10:30 Yoshikazu Terada: Local ordinal embedding
    10:30 - 11:30 Ulrike von Luxburg: Density estimation from unweighted kNN graphs
    12:30 - 13:15 Sven Kurras: The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation
    13:15 - 13:45 Morteza Alamgir: Density-preserving quantization with application to graph downsampling
  • 15.5.2014 Talk by Daniel Schmidtke about his master thesis (from 15:00-15:30). Then we discuss the paper by Dejan Slepcev et al, Continuum limit of total variation on point clouds. Preprint, 2014
  • 22.5.2014 Paper discussion: Breaking the Small Cluster Barrier of Graph Clustering, Nir Ailon, Yudong Chen, Huan Xu, ICML 2013 pdf
  • 17.4.2014 Paper discussion: Senelle, Garcia-Diez, Mantrach, Shimbo, Saerens, Fouss: The sum over forests density index: identifying dense regions in a graph. Preprint, 2013, not online yet, here is a local copy (with our usual login and password used for teaching). pdf
  • 24.4. 2014: talk by Sharon Bruckner (FU Berlin) about "Random-walk based methods for clustering"
  • 10.4.2014 Paper discussion: A Local Algorithm for Finding Well-Connected Clusters, Zeyuan Allen Zhu, Silvio Lattanzi, Vahab Mirrokni, ICML 2013 pdf
  • 3.4.2014 Paper discussion: Two papers on peer grading: Piech, Koller at al. Tuned Models of Peer Assessment in MOOCs pdf Shah, Wainwright et al A Case for Ordinal Peer-evaluation in MOOCs pdf
  • 23.1. 2014 Dominik Herrmann is going to talk about his PhD thesis. He used machine learning methods to investigate the computer security issues.
  • 9.1.2014 Tutorial by Sven Kurras on the mean shift algorithm
  • 21.11. 2013 Paper discussion: Estimating Unknown Sparsity in Compressed Sensing, Miles Lopes, ICML 2013 pdf
  • 14.11. 2013 Paper discussion: Efficient Ranking from Pairwise Comparisons, Fabian Wauthier, Michael Jordan, Nebojsa Jojic, ICML 2013 pdf
  • 7.11.2013 Paper discussion: Scalable Optimization of Neighbor Embedding for Visualization, Zhirong Yang, Jaakko Peltonen, Samuel Kaski, ICML 2013 pdf
  • 31.10.2013 Maximum Variance Correction with Application to A* Search, Wenlin Chen, Kilian Weinberger, Yixin Chen, ICML 2013 pdf
  • 25.10. 2013: Talk by Gina Gruenhage (TU Berlin). New data visualizations using cMDS: Embedding high dimensional data in a space of curves.
  • 18.10.2013 Paper discussion: Robust Structural Metric Learning, Daryl Lim, Gert Lanckriet, Brian McFee, ICML 2013 pdf
  • 11.10. 2013 Paper discussion: Vanishing Component Analysis, Roi Livni, David Lehavi, Sagi Schein, Hila Nachliely, Shai Shalev-Shwartz, Amir Globerson, best paper award at ICML 2013 pdf
  • 26.9.2013 (16:45) Talk by Julian Busch: Randomized Algorithms for Balanced Graph Cuts (defense of his Bachelor Thesis).
  • 15.7.2013 Talk by Cheng Soon Ong, Nicta Melbourne
  • 10.7.2013 Paper discussion: Local equivalences of distances between clusterings - A geometric perspective. Learning Journal, 2011 pdf
  • 3.7. 2013 Paper discussion: On the Hardness of Domain Adaptataion (And the Utility of Unlabeled Target Samples). ALT 2012 pdf
  • 19.6. 2013 Paper discussion: Statistical Consistency of Ranking Methods in A Rank-Differentiable Probability Space. NIPS 2012 pdf
  • 11.6.2013 Talk by Antoine Channarond
  • 4.6.2013 Talk by Yoshikazu Terada
  • 8.5.2013: Paper discussion: Sparse Algorithms are not Stable: A No-free-lunch Theorem. PAMI 2012. link
  • 24.4. 2013: Paper discussion: Convergence and Energy Landscape for Cheeger Cut Clustering, NIPS 2012 link
  • 6.3. 2013 Paper discussion: Clustering Sparse Graphs, NIPS 2012 link
  • 3.4.2013 Paper discussion: Semi-supervised Eigenvectors for Locally-biased Learning, NIPS 2012 link
  • 10.4.2013 Paper discussion: Learning with Partially Absorbing Random Walks, NIPS 2012 link
  • 27.2.2013: Paper discussion: Clustering by Nonnegative Matrix Factorization Using Graph Random Walks. NIPS 2012 link
  • 28.11.2012: Paper discussion: Maria A. Riolo, Mark Newman: First-principles multiway spectral partitioning of graphs. Arxiv, 2012
  • 14.11.2012: Paper discussion: J. Lee, S. Gharan, L. Trevisan. Multi-way spectral partitioning and higher-order Cheeger inequalities. STOC 2012.
  • 7.11.2012: Paper discussion: S. Dasgupta. Consistency of nearest neighbor classification under selective sampling. Twenty-Fifth Conference on Learning Theory (COLT) 2012.
  • 31.10.2012: Paper discussion: A. Barabasi et al. Controllability of complex networks. Nature 2011.