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Tech Xplore1d
Bilinear sequence regression model shows why AI excels at learning from word sequences
Researchers at EPFL have created a mathematical model that helps explain how breaking language into sequences makes modern AI ...
IEEE1d
Very short term forecasting in global solar irradiance using linear and nonlinear models
Very short term forecasting models can be useful to improve the available supplies. Present proposal allows a first approach for term shorter prediction of global solar irradiance. Linear and ...
GitHub12d
A python library to build Model Trees with Linear Models at the leaves.
Linear Trees combine the learning ability of Decision Tree with the predictive and explicative power of Linear Models. Like in tree-based algorithms, the data are split according to simple decision ...
C&EN17d
Use of a Nonnegative Constrained Principal Component Regression Chemical Mass Balance Model to Study the Contributions of Nearly Collinear Sources
In this study, a nonnegative constrained principal component regression chemical mass balance (NCPCRCMB) model was used to solve the near collinearity problem among source profiles for source ...
GitHub26d
kept getting this error with openai models
services.llm.LLMRetryError: Failed to make API call after 2 attempts. Last error: litellm.AuthenticationError: AnthropicException - b'{"type":"error","error":{"type ...
IEEE29d
A Study of Minimum Classification Error (MCE) Linear Regression for Supervised Adaptation of MCE-Trained Continuous-Density Hidden Markov Models
Abstract: In this paper, we present a formulation of minimum classification error linear regression (MCELR) for the adaptation of Gaussian mixture continuous-density ...