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US20090089230 COMPUTER GAME WITH INTUITIVE LEARNING CAPABILITY  
A computer game and a method of providing learning capability thereto are provided. The computer game has an objective of matching a skill level of the computer game with a skill level of a game...
US20150052092 METHODS AND SYSTEMS OF BRAIN-LIKE COMPUTING VIRTUALIZATION  
The invention discloses the technology of brain-like computing virtualization. Brain-like computing means the computing technology to mimic human brain and generate human intelligence...
US20120246102 ADAPTIVE ANALYTICAL BEHAVIORAL AND HEALTH ASSISTANT SYSTEM AND RELATED METHOD OF USE  
This present disclosure relates to systems and methods for providing an Adaptive Analytical Behavioral and Health Assistant. These systems and methods may include collecting one or more of patient...
US20150052094 POST GHOST PLASTICITY  
Methods and apparatus are provided for inferring and accounting for missing post-synaptic events (e.g., a post-synaptic spike that is not associated with any pre-synaptic spikes) at an artificial...
US20150248118 SYSTEMS AND METHODS FOR MODELING ENERGY CONSUMPTION AND CREATING DEMAND RESPONSE STRATEGIES USING LEARNING-BASED APPROACHES  
According to various implementations, a demand response (DR) strategy system is described that can effectively model the HVAC energy consumption of a house using a learning based approach that is...
US20150019468 THERMODYNAMIC COMPUTING  
Methods and systems for thermodynamic computing based on the attractor dynamics of volatile dissipative electronics attempting to maximize circuit power consumption. A general model of memristive...
US20130159231 MULTI-MODAL NEURAL NETWORK FOR UNIVERSAL, ONLINE LEARNING  
In one embodiment, the present invention provides a neural network comprising multiple modalities. Each modality comprises multiple neurons. The neural network further comprises an interconnection...
US20130226851 METHOD AND APPARATUS FOR MODELING NEURAL RESOURCE BASED SYNAPTIC PLACTICITY  
Certain aspects of the present disclosure support a method of designing the resource model in hardware (or software) for learning spiking neural networks. The present disclosure comprises...
US20150213356 METHOD FOR CONVERTING VALUES INTO SPIKES  
A method for transmitting values in a neural network includes obtaining a parameter value. The method also includes encoding the parameter value based on at least one value used by a neuron. The...
US20150161506 EFFECTING MODULATION BY GLOBAL SCALAR VALUES IN A SPIKING NEURAL NETWORK  
Methods and apparatus are provided for effecting modulation using global scalar values in a spiking neural network. One example method for operating an artificial nervous system generally includes...
US20100057654 SELF-LEARNING SYSTEM AND METHOD FOR PROVIDING A LOTTERY TICKET AT A POINT OF SALE DEVICE  
A system for managing a purchase agreement, including: a memory element for at least one specially-programmed general purpose computer, for storing an artificial intelligence program (AIP), and a...
US20130325775 DYNAMICALLY RECONFIGURABLE STOCHASTIC LEARNING APPARATUS AND METHODS  
Generalized learning rules may be implemented. A framework may be used to enable adaptive signal processing system to flexibly combine different learning rules (supervised, unsupervised,...
US20120290512 Methods for creating a situation dependent library of affective response  
Generating a situation-dependent library comprising a user's expected response to tokens representing stimuli that influence the user's affective state, including: receiving samples comprising...
US20140258194 GENERIC METHOD FOR DESIGNING SPIKE-TIMING DEPENDENT PLASTICITY (STDP) CURVES  
Methods and apparatus are provided for designing spike-timing dependent plasticity (STDP) curves whose parameter values are based on a set of equations. One example method generally includes...
US20150006454 NETWORK-PROBABILITY RECOMMENDATION SYSTEM  
A method/apparatus/system for generating a recommendation based on user interactions with nodes and associated tasks within a prerequisite graph. The recommendation is generated by identifying the...
US20150134582 IMPLEMENTING SYNAPTIC LEARNING USING REPLAY IN SPIKING NEURAL NETWORKS  
Aspects of the present disclosure relate to methods and apparatus for training an artificial nervous system. According to certain aspects, timing of spikes of an artificial neuron during a...
US20140250039 UNSUPERVISED, SUPERVISED AND REINFORCED LEARNING VIA SPIKING COMPUTATION  
The present invention relates to unsupervised, supervised and reinforced learning via spiking computation. The neural network comprises a plurality of neural modules. Each neural module comprises...
US20130073493 UNSUPERVISED, SUPERVISED, AND REINFORCED LEARNING VIA SPIKING COMPUTATION  
The present invention relates to unsupervised, supervised and reinforced learning via spiking computation. The neural network comprises a plurality of neural modules. Each neural module comprises...
US20140032463 ACCURATE AND FAST NEURAL NETWORK TRAINING FOR LIBRARY-BASED CRITICAL DIMENSION (CD) METROLOGY  
Approaches for accurate neural network training for library-based critical dimension (CD) metrology are described. Approaches for fast neural network training for library-based CD metrology are...
US20120226644 Accurate and Fast Neural network Training for Library-Based Critical Dimension (CD) Metrology  
Approaches for accurate neural network training for library-based critical dimension (CD) metrology are described. Approaches for fast neural network training for library-based CD metrology are...
US20140129498 METHOD FOR NON-SUPERVISED LEARNING IN AN ARTIFICIAL NEURAL NETWORK BASED ON MEMRISTIVE NANODEVICES, AND ARTIFICIAL NEURAL NETWORK IMPLEMENTING SAID METHOD  
An unsupervised learning method is provided implemented in an artificial neural network based on memristive devices. It consists notably in producing an increase in the conductance of a synapse...
US20120109865 USING AFFINITY MEASURES WITH SUPERVISED CLASSIFIERS  
A non-binary affinity measure between any two data points for a supervised classifier may be determined. For example, affinity measures may be determined for tree, kernel-based, nearest...
US20130268472 ARTIFICIAL INTELLIGENCE AND METHODS FOR RELATING HERBAL INGREDIENTS WITH ILLNESSES IN TRADITIONAL CHINESE MEDICINE  
Described herein are systems and methods for identifying herbal ingredients effective in treating illnesses in Traditional Chinese Medicine (TCM) using an artificial neural network.
US20140114893 LOW-POWER EVENT-DRIVEN NEURAL COMPUTING ARCHITECTURE IN NEURAL NETWORKS  
A neural network includes an electronic synapse array of multiple digital synapses interconnecting a plurality of digital electronic neurons. Each synapse interconnects an axon of a pre-synaptic...
US20130046716 METHOD AND APPARATUS FOR NEURAL TEMPORAL CODING, LEARNING AND RECOGNITION  
Certain aspects of the present disclosure support a technique for neural temporal coding, learning and recognition. A method of neural coding of large or long spatial-temporal patterns is also...
US20150095273 AUTOMATED METHOD FOR MODIFYING NEURAL DYNAMICS  
A method for improving neural dynamics includes obtaining prototypical neuron dynamics. The method also includes modifying parameters of a neuron model so that the neuron model matches the...
US20140344202 NEURAL MODEL FOR REINFORCEMENT LEARNING  
A neural model for reinforcement-learning and for action-selection includes a plurality of channels, a population of input neurons in each of the channels, a population of output neurons in each...
US20130339280 LEARNING SPIKE TIMING PRECISION  
Certain aspects of the present disclosure provide methods and apparatus for learning or determining delays between neuron models so that the uncertainty in input spike timing is accounted for in...
US20120303566 METHOD AND APPARATUS FOR UNSUPERVISED TRAINING OF INPUT SYNAPSES OF PRIMARY VISUAL CORTEX SIMPLE CELLS AND OTHER NEURAL CIRCUITS  
Certain aspects of the present disclosure present a technique for unsupervised training of input synapses of primary visual cortex (V1) simple cells and other neural circuits. The proposed...
US20120290513 Habituation-compensated library of affective response  
Generating a habituation-compensated library comprising a user's expected response to tokens representing stimuli that influence the user's affective state, the method comprising: receiving...
US20150248609 NEURAL NETWORK ADAPTATION TO CURRENT COMPUTATIONAL RESOURCES  
Methods and apparatus are provided for processing in an artificial nervous system. According to certain aspects, resolution of one or more functions performed by processing units of a neuron model...
US20140032461 SYNAPSE MAINTENANCE IN THE DEVELOPMENTAL NETWORKS  
The developmental neural network is trained using a synaptic maintenance process. Synaptogenic trimming is first performed on the neuron inputs using a synaptogenic factor for each neuron based on...
US20140188771 NEUROMORPHIC AND SYNAPTRONIC SPIKING NEURAL NETWORK CROSSBAR CIRCUITS WITH SYNAPTIC WEIGHTS LEARNED USING A ONE-TO-ONE CORRESPONDENCE WITH A SIMULATION  
Embodiments of the invention provide neuromorphic-synaptronic systems, including neuromorphic-synaptronic circuit chips implementing spiking neural network with synaptic weights learned using...
US20150026110 SPIKING MODEL TO LEARN ARBITRARY MULTIPLE TRANSFORMATIONS FOR A SELF-REALIZING NETWORK  
A neural network, wherein a portion of the neural network comprises: a first array having a first number of neurons, wherein the dendrite of each neuron of the first array is provided for...
US20110131166 FUZZY USERS' ATTRIBUTES PREDICTION BASED ON USERS' BEHAVIORS  
A method, apparatus, system, article of manufacture, and computer readable storage medium provide the ability to predict and utilize a user's attributes. A sample user behavior and a sample user...
US20150170027 NEURONAL DIVERSITY IN SPIKING NEURAL NETWORKS AND PATTERN CLASSIFICATION  
A method for providing diversity in a set of neurons in a neuron model includes retrieving a set of parameters for the set of neurons. The method also includes perturbing the set of parameters...
US20120109864 NEUROMORPHIC AND SYNAPTRONIC SPIKING NEURAL NETWORK WITH SYNAPTIC WEIGHTS LEARNED USING SIMULATION  
Embodiments of the invention provide neuromorphic-synaptronic systems, including neuromorphic-synaptronic circuits implementing spiking neural network with synaptic weights learned using...
US20150242744 STOCHASTIC DELAY PLASTICITY  
A method of operating a spiking neural network having neurons coupled together with a synapse includes monitoring a timing of a presynaptic spike and monitoring a timing of a postsynaptic spike....
US20150019467 FRAMEWORK FOR THE EVOLUTION OF ELECTRONIC NEURAL ASSEMBLIES TOWARD DIRECTED GOALS  
Methods and systems for the evolution of electronic neural assemblies toward directed goals. A compact computing architecture includes electronics that allows users of such an architecture to...
US20130138589 EXPLOITING SPARSENESS IN TRAINING DEEP NEURAL NETWORKS  
Deep Neural Network (DNN) training technique embodiments are presented that train a DNN while exploiting the sparseness of non-zero hidden layer interconnection weight values. Generally, a fully...
US20150242745 EVENT-BASED INFERENCE AND LEARNING FOR STOCHASTIC SPIKING BAYESIAN NETWORKS  
A method of performing event-based Bayesian inference and learning includes receiving input events at each node. The method also includes applying bias weights and/or connection weights to the...
US20090228415 MULTILAYER TRAINING IN A PHYSICAL NEURAL NETWORK FORMED UTILIZING NANOTECHNOLOGY  
A method for and system for training a connection network located between neuron layers within a multi-layer physical neural network. A multi-layer physical neural network can be formed having a...
US20150206049 MONITORING NEURAL NETWORKS WITH SHADOW NETWORKS  
A method for generating an event includes monitoring a first neural network with a second neural network. The method also includes generating an event based at least in part on the monitoring. The...
US20120041797 PROGRESS MONITORING METHOD  
The progress monitoring method is based on a critical path method (CPM) and conducts comparisons against multiple possible outcomes utilizing neural networks that classify planned progress at...
US20080294580 Neuromorphic Device for Proofreading Connection Adjustments in Hardware Artificial Neural Networks  
A hardware-implemented method for proofreading updates of connections in a hardware artificial neural network (hANN) includes computing a draft weight change independently at a connection between...
US20150081606 Reduction of Computation Complexity of Neural Network Sensitivity Analysis  
As part of neural network sensitivity analysis, base outputs of hidden layer nodes of a neural network model for non-perturbed variables can be reused when perturbing the variables. Such an...
US20120011088 COMMUNICATION AND SYNAPSE TRAINING METHOD AND HARDWARE FOR BIOLOGICALLY INSPIRED NETWORKS  
Certain embodiments of the present disclosure support techniques for training of synapses in biologically inspired networks. Only one device based on a memristor can be used as a synaptic...
US20120254086 DEEP CONVEX NETWORK WITH JOINT USE OF NONLINEAR RANDOM PROJECTION, RESTRICTED BOLTZMANN MACHINE AND BATCH-BASED PARALLELIZABLE OPTIMIZATION  
A method is disclosed herein that includes an act of causing a processor to access a deep-structured, layered or hierarchical model, called deep convex network, retained in a computer-readable...
US20130282634 DEEP CONVEX NETWORK WITH JOINT USE OF NONLINEAR RANDOM PROJECTION, RESTRICTED BOLTZMANN MACHINE AND BATCH-BASED PARALLELIZABLE OPTIMIZATION  
A method is disclosed herein that includes an act of causing a processor to access a deep-structured, layered or hierarchical model, called a deep convex network, retained in a computer-readable...
US20130018833 NEURAL NETWORK SYSTEM AND METHOD FOR CONTROLLING OUTPUT BASED ON USER FEEDBACK  
For various information sources, information output based on user feedback about information from the sources is controlled. A neural network module selects object(s) to receive information from...