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pro vyhledávání: '"Cvitkovic, Milan"'
We propose TabTransformer, a novel deep tabular data modeling architecture for supervised and semi-supervised learning. The TabTransformer is built upon self-attention based Transformers. The Transformer layers transform the embeddings of categorical
Externí odkaz:
http://arxiv.org/abs/2012.06678
Autor:
Cvitkovic, Milan
The majority of data scientists and machine learning practitioners use relational data in their work [State of ML and Data Science 2017, Kaggle, Inc.]. But training machine learning models on data stored in relational databases requires significant d
Externí odkaz:
http://arxiv.org/abs/2002.02046
We introduce SLM Lab, a software framework for reproducible reinforcement learning (RL) research. SLM Lab implements a number of popular RL algorithms, provides synchronous and asynchronous parallel experiment execution, hyperparameter search, and re
Externí odkaz:
http://arxiv.org/abs/1912.12482
Bayesian learning of model parameters in neural networks is important in scenarios where estimates with well-calibrated uncertainty are important. In this paper, we propose Bayesian quantized networks (BQNs), quantized neural networks (QNNs) for whic
Externí odkaz:
http://arxiv.org/abs/1912.02992
Autor:
Cvitkovic, Milan, Koliander, Günther
We introduce Minimal Achievable Sufficient Statistic (MASS) Learning, a training method for machine learning models that attempts to produce minimal sufficient statistics with respect to a class of functions (e.g. deep networks) being optimized over.
Externí odkaz:
http://arxiv.org/abs/1905.07822
We introduce the variational filtering EM algorithm, a simple, general-purpose method for performing variational inference in dynamical latent variable models using information from only past and present variables, i.e. filtering. The algorithm is de
Externí odkaz:
http://arxiv.org/abs/1811.05090
Autor:
Cvitkovic, Milan
Based on 46 in-depth interviews with scientists, engineers, and CEOs, this document presents a list of concrete machine research problems, progress on which would directly benefit tech ventures in East Africa.
Comment: Presented at NIPS 2018 Wor
Comment: Presented at NIPS 2018 Wor
Externí odkaz:
http://arxiv.org/abs/1810.11383
Machine learning models that take computer program source code as input typically use Natural Language Processing (NLP) techniques. However, a major challenge is that code is written using an open, rapidly changing vocabulary due to, e.g., the coinag
Externí odkaz:
http://arxiv.org/abs/1810.08305
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