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2. BDD-Guided Clause Generation

3. Insights into Parallelism with Intensive Knowledge Sharing

4. Parallel Combinatorial Optimization with Decision Diagrams

6. Snappy: A Simple Algorithm Portfolio

7. Stronger Inference through Implied Literals from Conflicts and Knapsack Covers

8. Parallel SAT Solver Selection and Scheduling

9. SatX10: A Scalable Plug&Play Parallel SAT Framework : (Tool Presentation)

10. Guiding Combinatorial Optimization with UCT

11. Algorithm Selection and Scheduling

12. Constraint Reasoning and Kernel Clustering for Pattern Decomposition with Scaling

13. An Empirical Study of Optimization for Maximizing Diffusion in Networks

14. An Empirical Study of Optimal Noise and Runtime Distributions in Local Search

15. Backdoors in the Context of Learning

16. Relaxed DPLL Search for MaxSAT

17. Backdoors to Combinatorial Optimization: Feasibility and Optimality

18. Filtering Atmost1 on Pairs of Set Variables

19. Connections in Networks: A Hybrid Approach

20. Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting

21. Short XORs for Model Counting: From Theory to Practice

22. Connections in Networks: Hardness of Feasibility Versus Optimality

23. Tradeoffs in the Complexity of Backdoor Detection

24. Revisiting the Sequence Constraint

25. QBF Modeling: Exploiting Player Symmetry for Simplicity and Efficiency

26. On the Hardness of Embeddings Between Two Finite Metrics

28. Learning Back-Clauses in SAT : (Poster Presentation)

29. Augmenting Clause Learning with Implied Literals : (Poster Presentation)

30. Non-Model-Based Algorithm Portfolios for SAT

31. Paper Retraction: On the Hardness of Embeddings Between Two Finite Metrics

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