#### Filter Results:

- Full text PDF available (5)

#### Publication Year

2004

2016

- This year (0)
- Last 5 years (3)
- Last 10 years (6)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

- Ehsan Amiri, Gábor Tardos
- SODA
- 2009

Including a unique code in each copy of a distributed document is an effective way of fighting intellectual piracy. Codes designed for this purpose that are secure against collusion attacks are called fingerprinting codes. In this paper we consider fingerprinting with the marking assumption and design codes that achieve much higher rates than previous… (More)

- Ehsan Amiri, Evgeny S. Skvortsov
- CSR
- 2007

We propose a simple modification of a well-known Random Walk algorithm for solving the Satisfiability problem and analyze its performance on random CNFs with a planted solution. We rigorously prove that the new algorithm solves the Full CNF with high probability, and for random CNFs with a planted solution of high density finds an assignment that differs… (More)

- Robert D. Cameron, Ehsan Amiri, Kenneth S. Herdy, Dan Lin, Thomas C. Shermer, Fred Popowich
- Euro-Par
- 2011

A parallel scanning method using the concept of bitstream addition is introduced and studied in application to the problem of XML parsing and well-formedness checking. On processors supporting W -bit addition operations, the method can perform up to W finite state transitions per instruction. The method is based on the concept of parallel bitstream… (More)

- Ehsan Amiri, Shadi Mahmoudi
- Appl. Soft Comput.
- 2016

Probabilistic algorithms play a major role in computer science; for some problems, for example Identity Testing, there is no efficient deterministic algorithm, but instead there are quite efficient probabilistic ones. For some other problems like Primality, although we know the problem is in P, yet randomized algorithms are more efficient. Randomization is… (More)

It’s easy to check that any specific string of length n has probability at most (1 − δ), hence SV-sources are n log 1 1−δ -sources. Also recall that SV-sources are (k, l) block sources where k = l log 1 1−δ . Suppose δ = log 1 1−δ , then k = δl. Take a hash-based extractor E : {0, 1} × {0, 1} → {0, 1}. Here, our weak-source is a SVsource over the strings of… (More)

- ‹
- 1
- ›