13 citations · 14 across the 2 of their papers we have counts for
5 papers
AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles
Charles Weill, Javier Gonzalvo, Vitaly Kuznetsov +9
AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for automatically learning high-quality ensembles with minimal expert intervention. Our framework is inspire…
Foundations of Sequence-to-Sequence Modeling for Time Series
Vitaly Kuznetsov, Zelda Mariet
The availability of large amounts of time series data, paired with the performance of deep-learning algorithms on a broad class of problems, has recently led to significant interes…
Online Non-Additive Path Learning under Full and Partial Information
Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri +2
We study the problem of online path learning with non-additive gains, which is a central problem appearing in several applications, including ensemble structured prediction. We pre…
Theory and Algorithms for Forecasting Time Series
Vitaly Kuznetsov, Mehryar Mohri
We present data-dependent learning bounds for the general scenario of non-stationary non-mixing stochastic processes. Our learning guarantees are expressed in terms of a data-depen…
Sums of Ceiling Functions Solve Nested Recursions
Rafal Drabek, Abraham Isgur, Vitaly Kuznetsov +1
It is known that, for given integers s \geq 0 and j > 0, the nested recursion R(n) = R(n - s - R(n - j)) + R(n - 2j - s - R(n - 3j)) has a closed form solution for which a combinat…