Hi and welcome to my homepage! I am a Postdoctoral fellow at UC Berkeley affiliated with EECS and BAIR. My hosts are Tom Griffiths and Stuart Russel.

I received my PhD in computer science at the Weizmann Institute. My adviser was Uri Feige.  
Research Interests: Algorithm and uncertainty: Design and analysis of algorithms with uncertainty/randomness in their data,
sublinear-time algorithms for pattern recognition and data analysis, cognitive science and artificial intelligence,
cascading behavior in networks (in particular: Bootstrap Percolation).

        to predict behavior in the age of big data? Submitted.
       for the string matching problem. [PDF] Manuscript.
       and Kayhan Ozcimder. A graph-theoretic approach to multitasking. [PDF] NIPS, 2017 (oral presentation).
       The structure of goal systems predicts human performance. [PDF] CogSci, 2017.
         Inference in sparse graphs with pairwise measurements and side information. [PDF] AISTATS, 2018
  • Joe Halpern, Rafael Pass and Daniel Reichman. On the non-existence of Nash equilibrium in games with resource-bounded
       players. [PDF] Submitted.
        arrays[PDF]  ICALP, 2017 (Track A).
       treewidth graphs. [PDF] SODA, 2017.
       Accepted to Random Structures and Algorithms.
       Combinatorics, to appear.
       From the Gaussian hidden clique problem to rank one perturbations of Gaussian tensors. [PDF] NIPS, 2015.
       Annals of Applied Probability. Video
       [PDF] SODA, 2015.
       [PDF] Random Structures and Algorithms, 2015.
        SIAM Journal of Discrete Mathematics, 2015. Preliminary version: RANDOM, 2014.
         Journal of Physics: Conference Series, 2013.
       International Journal of Computer Vision, 2017. Preliminary version: CVPR, 2013. 
  • Uriel Feige and Daniel Reichman. Recoverable values for independent sets. [PDF] Random Structures and
        Algorithms 2013.  Preliminary version: ICALP, 2011.
  • Daniel Reichman, New bounds for contagious sets. Discrete Mathematics, 2012.
  • Zeev Nutov and Daniel Reichman, Approximating maximum satisfiable subsystems of linear equations of
       bounded width. [PDF] Information Processing Letters, 2008.
  • Uriel Feige and Daniel Reichman, On the hardness of approximating Max-Satisfy.
       Information Processing Letters, 2006.
  • Uriel Feige and Daniel Reichman: On Systems of Linear Equations with Two Variables per Equation. APPROX,

Selected Talks:

  • Princeton CS theory seminar. "A Graph Theoretic Approach for Multitasking". October, 2017.
  • Redwood Center for Theoretical Neuroscience, Redwood-Griffiths Summit, "A Graph Theoretic Approach for Multitasking". 
        April, 2017.
  • UCSD, CS theory seminar, "On Percolation and NP-hardness". September, 2016.
  • University of Chicago,  CS theory seminar, "The layers model, with applications". November, 2013.     
  •  Gerogia Tech, Combinatorics seminar,  "Smoothed analysis on connected graphs". November, 2013.
  •  Microsoft Research, SVC, theory seminar,  "Smoothed analysis on connected graphs". November, 2013.
  •  Princeton University, Theory lunch, "The layers model, with applications". November, 2013. 
  •  Weizmann Institute, CS theory seminar, "Smoothed analysis on connected graphs". October 2013  
  •  Cornell University, CS theory seminar, "Contagious sets in expanders". May, 2013.
  •  Harvard University, Theory of computation seminar, "Contagious sets in expanders". May, 2013. 
  •  Freie University, Berlin, Combinatorics seminar, "Random permutations and random subgraphs".  April  2012. 
  •  Max Planck Institute for Human DevelopmentBerlin, Adaptive Behavior and Cognition, Group seminar, "Complexity: A theoretical analysis with applications to self regulation and goal pursuit".  April 2012. 
  • Canadam, 2015. Speaker at the minisymposium "probabilistic combinatorics".
  • Summer Institute on Bounded Rationality, Adaptive Behavior and Cognition group, Max Planck Institute for Human Development, Berlin, 2009.

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