In this paper, we establish a novel connection between total variation (...
We introduce the problem of active causal structure learning with advice...
This paper considers the problem of testing the maximum in-degree of the...
Interpretations of logical formulas over semirings have applications in
...
Modern machine learning approaches excel in static settings where a larg...
We propose a new causal inference framework to learn causal effects from...
We study two problems related to recovering causal graphs from intervent...
Total variation distance (TV distance) is a fundamental notion of distan...
We study the following independence testing problem: given access to sam...
We study the problem of testing whether a function f: ℝ^n →ℝ is a polyno...
A universal 1-bit compressive sensing (CS) scheme consists of a
measurem...
We consider the problem of efficiently inferring interventional distribu...
Gaussian Bayesian networks (a.k.a. linear Gaussian structural equation
m...
We study identifiability of Andersson-Madigan-Perlman (AMP) chain graph
...
Constraint satisfaction problems (CSP's) and data stream models are two
...
We study the problems of identity and closeness testing of n-dimensional...
A vehicle's fuel consumption depends on its type, the speed, the conditi...
We provide finite sample guarantees for the classical Chow-Liu algorithm...
In this paper, we study high-dimensional estimation from truncated sampl...
We design efficient distance approximation algorithms for several classe...
We study the problem of efficiently estimating the effect of an interven...
A code is called a q-query locally decodable code (LDC) if there is a
ra...
The k-Even Set problem is a parameterized variant of the Minimum Distanc...
We identify a new notion of pseudorandomness for randomness sources, whi...
We consider testing and learning problems on causal Bayesian networks as...
The k-Even Set problem is a parameterized variant of the Minimum Distanc...
We prove the hardness of weakly learning halfspaces in the presence of
a...
We investigate the problem of winner determination from computational so...