Zobrazeno 1 - 10
of 43
pro vyhledávání: '"BŁASIOK, JAROSŁAW"'
We give a simple, greedy $O(n^{\omega+0.5})=O(n^{2.872})$-time algorithm to list-decode planted cliques in a semirandom model introduced in [CSV17] (following [FK01]) that succeeds whenever the size of the planted clique is $k\geq O(\sqrt{n} \log^2 n
Externí odkaz:
http://arxiv.org/abs/2404.14159
Autor:
Błasiok, Jarosław, Nakkiran, Preetum
Calibration measures and reliability diagrams are two fundamental tools for measuring and interpreting the calibration of probabilistic predictors. Calibration measures quantify the degree of miscalibration, and reliability diagrams visualize the str
Externí odkaz:
http://arxiv.org/abs/2309.12236
Optimizing proper loss functions is popularly believed to yield predictors with good calibration properties; the intuition being that for such losses, the global optimum is to predict the ground-truth probabilities, which is indeed calibrated. Howeve
Externí odkaz:
http://arxiv.org/abs/2305.18764
Multicalibration is a notion of fairness for predictors that requires them to provide calibrated predictions across a large set of protected groups. Multicalibration is known to be a distinct goal than loss minimization, even for simple predictors su
Externí odkaz:
http://arxiv.org/abs/2304.09424
Autor:
Alman, Josh, Błasiok, Jarosław
Three-player Number On the Forehead communication may be thought of as a three-player Number In the Hand promise model, in which each player is given the inputs that are supposedly on the other two players' heads, and promised that they are consisten
Externí odkaz:
http://arxiv.org/abs/2302.11476
We study the fundamental question of how to define and measure the distance from calibration for probabilistic predictors. While the notion of perfect calibration is well-understood, there is no consensus on how to quantify the distance from perfect
Externí odkaz:
http://arxiv.org/abs/2211.16886
We introduce and study the communication complexity of computing the inner product of two vectors, where the input is restricted w.r.t. a norm $N$ on the space $\mathbb{R}^n$. Here, Alice and Bob hold two vectors $v,u$ such that $\|v\|_N\le 1$ and $\
Externí odkaz:
http://arxiv.org/abs/2211.13473
Having similar behavior at training time and test time $-$ what we call a "What You See Is What You Get" (WYSIWYG) property $-$ is desirable in machine learning. Models trained with standard stochastic gradient descent (SGD), however, do not necessar
Externí odkaz:
http://arxiv.org/abs/2204.03230
Autor:
Błasiok, Jarosław, Ivanov, Peter, Jin, Yaonan, Lee, Chin Ho, Servedio, Rocco A., Viola, Emanuele
We analyze the Fourier growth, i.e. the $L_1$ Fourier weight at level $k$ (denoted $L_{1,k}$), of various well-studied classes of "structured" $\mathbb{F}_2$-polynomials. This study is motivated by applications in pseudorandomness, in particular rece
Externí odkaz:
http://arxiv.org/abs/2107.10797
We give a short argument that yields a new lower bound on the number of subsampled rows from a bounded, orthonormal matrix necessary to form a matrix with the restricted isometry property. We show that a matrix formed by uniformly subsampling rows of
Externí odkaz:
http://arxiv.org/abs/1903.12135