Share This Author
Towards Understanding and Harnessing the Potential of Clause Learning
- P. Beame, Henry A. Kautz, Ashish Sabharwal
- Computer ScienceJournal of Artificial Intelligence Research
- 1 July 2004
The first precise characterization of clause learning as a proof system (CL) is presented, and it is shown that with a new learning scheme, CL can provide exponentially shorter proofs than many proper refinements of general resolution satisfying a natural property.
Combining Component Caching and Clause Learning for Effective Model Counting
- T. Sang, F. Bacchus, P. Beame, Henry A. Kautz, T. Pitassi
- Computer ScienceInternational Conference on Theory and…
- 2004
A model-counting program that combines component caching with clause learning, one of the most important ideas used in modern SAT solvers, and provides significant evidence that it can outperform existing algorithms for #SAT by orders of magnitude.
Optimal Bounds for the Predecessor Problem and Related Problems
- P. Beame, Faith Ellen
- Mathematics, Computer ScienceJournal of computer and system sciences (Print)
- 1 August 2002
The lower bounds are proved for a large class of problems, including both static and dynamic predecessor problems, in a much stronger communication game model, but they apply to the cell probe and RAM models.
Communication steps for parallel query processing
- P. Beame, Paraschos Koutris, Dan Suciu
- Computer ScienceACM SIGACT-SIGMOD-SIGART Symposium on Principles…
- 22 June 2013
The problem of computing a relational query q on a large input database of size n, using a large number p of servers is considered, and it is shown that for the class of tree-like queries there exists a tradeoff between the number of rounds and the space exponent ε.
Log Depth Circuits for Division and Related Problems
This work presents optimal depth Boolean circuits for integer division, powering, and multiple products and describes an algorithm for testing divisibility that is optimal for both depth and space.
Performing Bayesian Inference by Weighted Model Counting
- T. Sang, P. Beame, Henry A. Kautz
- Computer ScienceAAAI Conference on Artificial Intelligence
- 9 July 2005
An efficient translation from Bayesian networks to weighted model counting, extend the best model-counting algorithms to weightedmodel counting, develop an efficient method for computing all marginals in a single counting pass, and evaluate the approach on computationally challenging reasoning problems.
Skew in parallel query processing
- P. Beame, Paraschos Koutris, Dan Suciu
- Computer ScienceACM SIGACT-SIGMOD-SIGART Symposium on Principles…
- 8 January 2014
A tight connection is established between the fractional edge packing of the query and the amount of communication in two cases, where the data is skewed and the heavy hitters and their frequencies are known.
Optimal bounds for the predecessor problem
- P. Beame, Faith Ellen
- Computer Science, MathematicsSTOC '99
- 1 May 1999
The upper and lower bounds for the amount of time to find the predecessor of a given element among the elements of a fixed efficiently stored set are obtained and apply to the cell probe and RAM models and to both static and dynamic predecessor problems.
Model checking large software specifications
- William Chan, Richard J. Anderson, J. Reese
- Computer ScienceSIGSOFT '96
- 1 October 1996
The results and experiences of using symbolic model checking to study the specification of an aircraft collision avoidance system and the approach to translating the specification to the SMV language and methods for achieving acceptable performance are reported.
Worst-Case Optimal Algorithms for Parallel Query Processing
- P. Beame, Paraschos Koutris, Dan Suciu
- Computer ScienceInternational Conference on Database Theory
- 1 March 2016
This paper studies the communication complexity for the problem of computing a conjunctive query on a large database in a parallel setting with $p$ servers, and shows a surprising connection to the external memory model, which allows us to translate parallel algorithms to external memory algorithms.
...
...