Topic 1: Markov Decision Processes and Bandit Problems
- Main papers:
- J. N. Tsitsiklis, "A Short Proof of the Gittins Index Theorem", Annals of Applied Probability, Vol. 4, No. 1, 1994, pp. 194-199.
- T.L. Lai and Herbert Robbins, Asymptotically Efficient Adaptive Allocation Rules, Advances In Applied Mathemattcs 6,4-22
- Tze Leung Lai, Adaptive Treatment Allocation and the Multi-Armed Bandit Problem, The Annals of Statistics, Vol. 15, No. 3. (Sep., 1987), pp. 1091-1114.
- Abraham D. Flaxman, Adam Tauman Kalai, H. Brendan McMahan, Online convex optimization in the bandit setting: gradient descent without a gradient,
- Peter Auer, Nicol O Cesa-bianchi, Yoav Freund, Robert E. Schapire, The Nonstochastic Multiarmed Bandit Problem, SIAM Journal on Computing, Vol 32 (2002)
Topic 2: Optimization Relaxation Methods
- Main papers:
- Monique Laurent, A comparison of the Sherali-Adams, Lovasz-Schrijver and Lasserre relaxations for 0-1 programming, 2002
- L. Lovasz and A. Schrijver, Cones of matrices and set-functions and 0-1 optimization, SIAM J. Optim. 1 (1991), 166--190.
- M. Grotschel, L. Lovasz, and A. Schrijver, Polynomial algorithms for perfect graphs, Topics on perfect graphs, North-Holland Math. Stud., 88, North-Holland, Amsterdam-New York, 1984, pp. 325--356.
Topic 3: Good-Turing estimator
Topic 4: Graph convergence
- Main papers:
- L. Lovasz and B. Szegedy: Limits of dense graph sequences, J. Comb. Theory 96 (2006), 933-957.
- L. Lovasz and B. Szegedy: Szemeredi's Lemma for the analyst, J. Geom. and Func. Anal. 17 (2007), 252-270.
- L. Lovasz and B. Szegedy: Testing properties of graphs and functions,
- C. Borgs, J. Chayes, L. Lovasz, V.T. Sos and K. Vesztergombi: Convergent Sequences of Dense Graphs I: Subgraph Frequencies, Metric Properties and Testing,
- C. Borgs, J. Chayes, L. Lovasz, V.T. Sos and K. Vesztergombi: Convergent Sequences of Dense Graphs II: Multiway Cuts and Statistical Physics
Topic 5: Information-theoretic security and Cryptography
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