2009 CS Technical Reports
- CS-2009-01
Tamir Levi and Ami Litman:
On Fast Bitonic Sorting Networks
- CS-2009-02
Michael Kaminski and Tony Tan:
A note on two-pebble automata over infinite alphabets
- CS-2009-03
Tony Tan:
Graph Reachability and Pebble Automata over Infinite Alphabets
- CS-2009-04
Tony Tan:
A Logic for Graph with the Edges as the Domain
- CS-2009-05
Tony Tan:
On Pebble Automata for Data Languages with Decidable Emptiness Problem
- CS-2009-06
Ilan Gronau:
Bayesian Analysis Of Distance Estimation in the K2P Model.
- CS-2009-07
Tamir Levi and Ami Litman:
Lower Bounds On Bitonic Sorting Networks
- CS-2009-08
Eliyahu Osherovich, Michael Zibulevsky, and Irad Yavneh:
IMAGE RECONSTRUCTION FROM NOISY FOURIER MAGNITUDE WITH PARTIAL PHASE INFORMATION
- CS-2009-09
Eliyahu Osherovich, Michael Zibulevsky, and Irad Yavneh:
Signal Reconstruction From The Modulus of its Fourier Transform
- CS-2009-10
Tony Tan:
Determinizing two-way alternating pebble automata for data languages
- CS-2009-11
Ilan Gronau, Shlomo Moran and Irad Yavneh:
Adaptive Distance Measures for Resolving K2P Quartets: Metric Separation versus Stochastic Noise
- CS-2009-12
Eliyahu Osherovich:
Designing Optimal Projections for Compressed Sensing: Algorithm Comparison
- CS-2009-13
Ron Rubinstein, Michael Zibulevsky, Michael Elad:
Learning Sparse Dictionaries for Sparse Signal Approximation
- CS-2009-14
Yael Meller, Orna Grumberg and Sharon Shoham:
A Framework For Compositional Verification of Multi-Valued Systems Via Abstraction-Refinement
- CS-2009-15
Tamar Aizikowitz and Michael Kaminski:
Linear Conjunctive Grammars and One-turn Synchronized Alternating Pushdown Automata
- CS-2009-16
Eliyahu Osherovich, Michael Zibulevsky, and Irad Yavneh:
Fast Reconstruction Method for Diffraction Imaging
- CS-2009-17
Michael Zibulevsky:
How to relax an economic crisis using consumer insurance obligations
- CS-2009-18
Michael Zibulevsky:
How to prevent economic crisis in time of disaster: consumer insurance bonds
- CS-2009-19
Avishai Adler and Michael Zibulevsky:
Sparse Solution for the Intensity-Modulated Radiotherapy Problem Using Conic Programming
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