Search Results for author: Nikolai Yakovenko

Found 4 papers, 2 papers with code

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

1 code implementation3 Aug 2018 Raul Puri, Robert Kirby, Nikolai Yakovenko, Bryan Catanzaro

We provide a learning rate schedule that allows our model to converge with a 32k batch size.

Language Modelling

Practical Text Classification With Large Pre-Trained Language Models

1 code implementation4 Dec 2018 Neel Kant, Raul Puri, Nikolai Yakovenko, Bryan Catanzaro

Multi-emotion sentiment classification is a natural language processing (NLP) problem with valuable use cases on real-world data.

Emotion Classification General Classification +4

Poker-CNN: A Pattern Learning Strategy for Making Draws and Bets in Poker Games

no code implementations22 Sep 2015 Nikolai Yakovenko, Liangliang Cao, Colin Raffel, James Fan

The contributions of this paper include: (1) a novel representation for poker games, extendable to different poker variations, (2) a CNN based learning model that can effectively learn the patterns in three different games, and (3) a self-trained system that significantly beats the heuristic-based program on which it is trained, and our system is competitive against human expert players.

Game of Poker

Genome Variant Calling with a Deep Averaging Network

no code implementations13 Mar 2020 Nikolai Yakovenko, Avantika Lal, Johnny Israeli, Bryan Catanzaro

Variant calling, the problem of estimating whether a position in a DNA sequence differs from a reference sequence, given noisy, redundant, overlapping short sequences that cover that position, is fundamental to genomics.

Position

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