Duc Nghia Pham

Yasaman Eftekharypour

Ang Jia Pheng

Proceedings of the PRICAI 2019: Trends in Artificial Intelligence, 2019

2014

How Good Are Simplified Models for Protein Structure Prediction?

[BibT_eX]

[DOI]

Adv. Bioinformatics, 2014

2013

The road not taken: retreat and diverge in local search for simplified protein structure prediction.

[BibT_eX]

[DOI]

BMC Bioinform., 2013

Spiral search: a hydrophobic-core directed local search for simplified PSP on 3D FCC lattice.

[BibT_eX]

[DOI]

BMC Bioinform., 2013

Trap escape for local search by backtracking and conflict reverse.

[BibT_eX]

[DOI]

Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence, 2013

Weight-Enhanced Diversification in Stochastic Local Search for Satisfiability.

[BibT_eX]

[DOI]

Thach-Thao Nguyen Duong

M. A. Hakim Newton

Proceedings of the IJCAI 2013, 2013

Stochastic Local Search Based Channel Assignment in Wireless Mesh Networks.

[BibT_eX]

[DOI]

Proceedings of the Principles and Practice of Constraint Programming, 2013

A Hybrid Local Search for Simplified Protein Structure Prediction.

[BibT_eX]

Proceedings of the BIOINFORMATICS 2013 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms, Barcelona, Spain, 11, 2013

Diversify Intensification Phases in Local Search for SAT with a New Probability Distribution.

[BibT_eX]

[DOI]

Proceedings of the AI 2013: Advances in Artificial Intelligence, 2013

2012

A Study of Local Minimum Avoidance Heuristics for SAT.

[BibT_eX]

[DOI]

Muhammad Abdul Hakim Newton

Proceedings of the ECAI 2012, 2012

Memory-based local search for simplified protein structure prediction.

[BibT_eX]

[DOI]

Swakkhar Shatabda

Proceedings of the ACM International Conference on Bioinformatics, 2012

Random-walk: a stagnation recovery technique for simplified protein structure prediction.

[BibT_eX]

[DOI]

Proceedings of the ACM International Conference on Bioinformatics, 2012

A New Genetic Algorithm for Simplified Protein Structure Prediction.

[BibT_eX]

[DOI]

Proceedings of the AI 2012: Advances in Artificial Intelligence, 2012

A Method to Avoid Duplicative Flipping in Local Search for SAT.

[BibT_eX]

[DOI]

Proceedings of the AI 2012: Advances in Artificial Intelligence, 2012

Trap Avoidance in Local Search Using Pseudo-Conflict Learning.

[BibT_eX]

[DOI]

Muhammad Abdul Hakim Newton

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011

Kangaroo: An Efficient Constraint-Based Local Search System Using Lazy Propagation.

[BibT_eX]

[DOI]

Michael J. Maher

Proceedings of the Principles and Practice of Constraint Programming - CP 2011, 2011

2010

Partial Weighted MaxSAT for Optimal Planning.

[BibT_eX]

[DOI]

Proceedings of the PRICAI 2010: Trends in Artificial Intelligence, 2010

2009

SAT-Based Parallel Planning Using a Split Representation of Actions.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Automated Planning and Scheduling, 2009

2008

Combining Adaptive and Dynamic Local Search for Satisfiability.

[BibT_eX]

[DOI]

J. Satisf. Boolean Model. Comput., 2008

Modelling and solving temporal reasoning as propositional satisfiability.

[BibT_eX]

[DOI]

Artif. Intell., 2008

Using Cost Distributions to Guide Weight Decay in Local Search for SAT.

[BibT_eX]

[DOI]

Proceedings of the PRICAI 2008: Trends in Artificial Intelligence, 2008

A Compact and Efficient SAT Encoding for Planning.

[BibT_eX]

[DOI]

Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling, 2008

Efficiently Exploiting Dependencies in Local Search for SAT.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007

Building Structure into Local Search for SAT.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2007, 2007

Advances in Local Search for Satisfiability.

[BibT_eX]

[DOI]

Proceedings of the AI 2007: Advances in Artificial Intelligence, 2007

2006

Towards an Efficient SAT Encoding for Temporal Reasoning.

[BibT_eX]

[DOI]