We study the problem of learning parity functions that depend on at most $k$ variables ($k$-parities) attribute-efficiently in the mistake-bound model.
We design simple, deterministic, polynomial-time algorithms for learning $k$-parities with mistake bound $O(n^{1-\frac{c}{k}})$, for any constant $c > 0$. These are the first polynomial-time algorithms that learn $\omega(1)$-parities in ... more >>>

The well known dichotomy conjecture of Feder and
Vardi states that for every finite family Γ of constraints CSP(Γ) is
either polynomially solvable or NP-hard. Bulatov and Jeavons re-
formulated this conjecture in terms of the properties of the algebra
P ol(Γ), where the latter is ... more >>>

We present new deterministic algorithms for several cases of the maximum rank matrix completion
problem (for short matrix completion), i.e. the problem of assigning values to the variables in
a given symbolic matrix as to maximize the resulting matrix rank. Matrix completion belongs to
the fundamental problems in computational complexity ... more >>>