no code implementations • 20 Jan 2023 • Yair Neuman, Vladyslav Kozhukhov, Dan Vilenchik
Modeling human personality is important for several AI challenges, from the engineering of artificial psychotherapists to the design of persona bots.
no code implementations • 1 Aug 2022 • Michael Sidorov, Dan Vilenchik
We design several algorithms for this task, ranging from a simple greedy algorithm that only learns $u$'s conditional probability distribution, ignoring the rest of $V$, to a convolutional neural network-based algorithm that receives the activity of all of $V$, but does not receive explicitly the social link structure.
no code implementations • 26 May 2022 • Kiril Danilchenko, Michael Segal, Dan Vilenchik
We propose a new method for classifying reviewers as spammers or benign, combining machine learning with a message-passing algorithm that capitalizes on the users' graph structure to compensate for the possible scarcity of labeled data.
1 code implementation • 1 Dec 2021 • Ron Korenblum Pick, Vladyslav Kozhukhov, Dan Vilenchik, Oren Tsur
Our framework is unsupervised and domain-independent.
1 code implementation • 15 Oct 2019 • Guy Holtzman, Adam Soffer, Dan Vilenchik
The taxing computational effort that is involved in solving some high-dimensional statistical problems, in particular problems involving non-convex optimization, has popularized the development and analysis of algorithms that run efficiently (polynomial-time) but with no general guarantee on statistical consistency.
no code implementations • 16 Jun 2013 • Robert Krauthgamer, Boaz Nadler, Dan Vilenchik
In fact, we conjecture that in the single-spike model, no computationally-efficient algorithm can recover a spike of $\ell_0$-sparsity $k\geq\Omega(\sqrt{n})$.