Bangla natural language processing: A comprehensive analysis of classical, machine learning, and deep learning-based methods

O Sen, M Fuad, MN Islam, J Rabbi, M Masud… - IEEE …, 2022 - ieeexplore.ieee.org
The Bangla language is the seventh most spoken language, with 265 million native and non-
native speakers worldwide. However, English is the predominant language for online …

Comparative assessment of various machine learning‐based bias correction methods for numerical weather prediction model forecasts of extreme air temperatures in …

D Cho, C Yoo, J Im, DH Cha - Earth and Space Science, 2020 - Wiley Online Library
Forecasts of maximum and minimum air temperatures are essential to mitigate the damage
of extreme weather events such as heat waves and tropical nights. The Numerical Weather …

Comparison of machine learning algorithms for retrieval of water quality indicators in case-II waters: A case study of Hong Kong

S Hafeez, MS Wong, HC Ho, M Nazeer, J Nichol… - Remote sensing, 2019 - mdpi.com
Anthropogenic activities in coastal regions are endangering marine ecosystems. Coastal
waters classified as case-II waters are especially complex due to the presence of different …

Customer decision-making analysis based on big social data using machine learning: a case study of hotels in Mecca

A Alsayat - Neural Computing and Applications, 2023 - Springer
Big social data and user-generated content have emerged as important sources of timely
and rich knowledge to detect customers' behavioral patterns. Revealing customer …

[PDF][PDF] SVMTorch: Support vector machines for large-scale regression problems

R Collobert, S Bengio - Journal of machine learning research, 2001 - jmlr.org
Abstract Support Vector Machines (SVMs) for regression problems are trained by solving a
quadratic optimization problem which needs on the order of l2 memory and time resources …

Kernel association for classification and prediction: A survey

Y Motai - IEEE transactions on neural networks and learning …, 2014 - ieeexplore.ieee.org
Kernel association (KA) in statistical pattern recognition used for classification and prediction
have recently emerged in a machine learning and signal processing context. This survey …

Advanced support vector machines and kernel methods

VD Sánchez A - Neurocomputing, 2003 - Elsevier
Kernel methods (KMs) and support vector machines (SVMs) have become very popular as
methods for learning from examples. The basic theory is well understood and applications …

[图书][B] Neural networks in a softcomputing framework

KL Du, MNS Swamy - 2006 - Springer
Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

Training v-Support Vector Regression: Theory and Algorithms

CC Chang, CJ Lin - Neural computation, 2002 - direct.mit.edu
We discuss the relation betweenɛ-support vector regression (ɛ-SVR) and v-support vector
regression (v-SVR). In particular, we focus on properties that are different from those of C …

Parallel Gaussian process optimization with upper confidence bound and pure exploration

E Contal, D Buffoni, A Robicquet, N Vayatis - Joint European Conference …, 2013 - Springer
In this paper, we consider the challenge of maximizing an unknown function f for which
evaluations are noisy and are acquired with high cost. An iterative procedure uses the …