Class NipsCategories

  extended by org.knowceans.corpus.parsers.nips.NipsCategories

public class NipsCategories
extends java.lang.Object

Field Summary
(package private)  java.lang.String[] cats
          Categories for NIPS papers volumes 14-16.
Constructor Summary
Method Summary
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail


java.lang.String[] cats
Categories for NIPS papers volumes 14-16.

AA = Algorithms and Architectures: statistical learning algorithms, neural network architectures, kernel methods, graphical models, Gaussian processes, independent component analysis, model selection, active learning, combinatorial optimization.

AP = Applications: innovative applications or fielded systems that use machine learning, including time series, biological applications, text/web analysis, multimedia, robotics, or other intelligent systems.

CS = Cognitive Science/Artificial Intelligence: theoretical, computational, or experimental studies of perception, psychophysics, human or animal learning, memory, reasoning, problem solving, language, and neuropsychology.

IM = Emerging Technologies: analog and digital VLSI, neuromorphic engineering, computational sensors and actuators, microrobotics, bioMEMS, neural prostheses, photonics, molecular and quantum computing.

NS = Neuroscience: theoretical and experimental studies of encoding, decoding, processing, and transmission of information in biological neurons, including spike train generation, synaptic modulation, plasticity and adaptation, and network properties.

CN = Reinforcement Learning and Control: Markov decision processes, exploration, planning, navigation, game-playing, multi-agent coordination, computational models of classical and operant conditioning.

SP = Speech and Signal Processing: recognition, coding, synthesis, de-noising, source separation, auditory perception, psychoacoustics, temporal algorithms for signal processing such as Markov models, dynamical systems, recurrent networks.

LT = Theory: learning theory, information theory, statistical physics of learning, Bayesian methods, approximation bounds, online learning and dynamics, generalization and regularization.

VS = Visual Processing: image processing and coding, segmentation, object detection and recognition, motion detection and tracking, visual psychophysics, visual scene analysis and interpretation.

Constructor Detail


public NipsCategories()