Classifiers for Sensory Data (e.g. tanh( ) ) Key Signal to Symbol - PowerPoint PPT Presentation

Apr 08, 2023 •199 likes •289 views

Classifiers for Sensory Data (e.g. tanh( ) ) Key Signal to Symbol Refinement Two layers: (VMM + nonlinear functions) (e.g. tanh( ) ) Required for Universal Approximator = arbitrary function approximation with infinite (countable) neurons

Classifiers for Sensory Data (e.g. tanh( ) ) Key Signal to Symbol Refinement Two layers: (VMM + nonlinear functions) (e.g. tanh( ) ) Required for Universal Approximator = arbitrary function approximation with infinite (countable) neurons VMM = Vector Matrix Multiplication y = W x XOR: Classic VMM often implemented in FPAA function showing two layers Nonlinear function (e.g. tanh) allows required to for decisions and nonlinear function fully implement approximation
FG VMM VMM in FPAA Routing Fabric (Computing in memory) [Chawla, et. al, CICC 2004] Analog (VMM): ~10-20MMAC/ µ W ~50-100 fJ / MAC Digital ~ 10MMAC/mW @ yield
VMM + k-WTA: Experimental Measurements of Measured XOR Scatter Plot a Universal Approximator 1 single VMM + n-WTA layer = universal approximator [Ramakrishnan, et. al, 2013] [Maass, et. al, 2000] Also 3-Parity, 4-Parity WTA: biologically inspired, good framework for further bio-inspired computing
Classifiers Equivalences with VMM+WTA Invariance: • Constant Weight Offsets • Constant Weight Scaling • Constant Input Offsets � Only requires 1 quadrant mult Equivalence: • VQ • SOM • GMM
Measured XOR Classifier: Different CABs
SoC FPAA: Computing
Experiment Session Perform the 2-input VMM + WTA block for the XOR problem When you start your classifier, the weights might not be quite right. You should change these weights until you get the resulting function and take note of these differences

Recommend

A package for sensory data analysis with R scientific discipline that applies principals of

Sensory analysis Sensory Analysis (or Sensory Evaluation) is a A package for sensory data analysis with R scientific discipline that applies principals of experimental design and statistical analysis to the use of human senses (sight, smell,

551 views • 6 slides

Sensory Replacement What is it? Related Devices Can it be applied to the art world? Sensory

Sensory Replacement What is it? Related Devices Can it be applied to the art world? Sensory Alteration Sensory Replacement Sensory Enhancement Sensory Change Sensory Replacement Reason Idea behind it Examples Why? Absence/loss of

365 views • 22 slides

Nonlinear Classifiers II 2 Nonlinear Classifiers: Introduction Classifiers Supervised

1 Nonlinear Classifiers II 2 Nonlinear Classifiers: Introduction Classifiers Supervised Classifiers XOR problem Linear Classifiers Perceptron Least Squares Methods Linear Support Vector Machine Nonlinear

355 views • 20 slides

Sensory Processing Disorder Sensory Modulation Disorder - (Hyper / Hypo/ Seeking) Sensory

Sensory Processing Workshop Anita Bradshaw, M.Ed What is Sensory Processing ? Sensory Processing is... how your brain interprets messages about your senses. What do we mean by Sensory Processing Disorder? This is when messages about your senses

240 views • 6 slides

Bayes Classifiers Nave Bayes Classification Patrick Mair Bayes Classifiers Weather data

Bayes Classifiers Nave Bayes Classification Patrick Mair Bayes Classifiers Weather data set Predictors: Outlook, Temperature, Humidity, Windy. Response: Play (yes/no) Starting point Cross classification: Predictor/Response

98 views • 6 slides

Introduction to Sensory Processing Sensory Integration (SI) is the automatic ability to; What is

Introduction to Sensory Processing Sensory Integration (SI) is the automatic ability to; What is Sensory Receive Processing Disorder (SPD) Process Also known as Organise Sensory Integration Respond difficulties to the sensory

586 views • 13 slides

Industrial Sensory Data Analytics Introduction, Analysis Goals & Methods/Tools Industrial

Industrial Sensory Data Analytics Introduction, Analysis Goals & Methods/Tools Industrial Sensory Data Analytics Introduction Pattern Recognition in Time Series Data The field of Natural Language Processing (NLP) has seen a number of

428 views • 27 slides

SENSORY EVALUATION .. Basics of Sensory evaluation, Tools, Techniques, Methods and

SENSORY EVALUATION .. Basics of Sensory evaluation, Tools, Techniques, Methods and Interpretation 1 SENSORY EVALUATION Sensory evaluation is a scientific discipline that analyses and measures human responses to the composition and

758 views • 39 slides

Simple Solutions to Sensory Processing Issues Oh, so THATS WHY theyre melting down...

Simple Solutions to Sensory Processing Issues Oh, so THATS WHY theyre melting down... Introductions Cara from Health Home and Happiness Teresa, mom of 11 Its a sensory issue Sensory avoidant vs Sensory Seeking Can have both in

361 views • 18 slides

Sensory Processing, Self- Self-Regulation and Sensory Processing Sensory Motor Preferences

18/11/2019 GOALS : Sensory Processing, Self- Self-Regulation and Sensory Processing Sensory Motor Preferences Regulation Different Strategies to help develop self-regulation and sensory processing Presentation for Different

623 views • 11 slides

Enabling Innovation Getting Started With Sensory Evaluation Introduction I want to do some

Enabling Innovation Getting Started With Sensory Evaluation Introduction I want to do some sensory. What do you want to find out ? What will you use data for? What actions will you take in response to data? Introduction SUBJECTIVE

536 views • 51 slides

Sketching Linear Classifiers Over Data Streams Kai Sheng Tai Vatsal Sharan, Peter Bailis,

Sketching Linear Classifiers Over Data Streams Kai Sheng Tai Vatsal Sharan, Peter Bailis, Gregory Valiant Stanford University High-dimensional linear classifiers on streams Ubiquitous: spam detection, ad click prediction, network traffic

604 views • 28 slides

Occasion-level Classifiers or Event-level Classifiers? -Evidence from Child Language Acquisition

Occasion-level Classifiers or Event-level Classifiers? -Evidence from Child Language Acquisition Yuan Xiaohe, Zhang Xiaoqian, Luo Yingyi, Hu Jianhua Institute of Linguistics Chinese Academy of Social Sciences Verbal classifiers in Mandarin

823 views • 24 slides

Data Warehousing and Machine Learning Probabilistic Classifiers Thomas D. Nielsen Aalborg

Data Warehousing and Machine Learning Probabilistic Classifiers Thomas D. Nielsen Aalborg University Department of Computer Science Spring 2008 DWML Spring 2008 1 / 34 Probabilistic Classifiers Conditional class probabilities Id. Savings

761 views • 59 slides

Machine Learning Nave Bayes classifiers Types of classifiers We can divide the large

10-701 Machine Learning Nave Bayes classifiers Types of classifiers We can divide the large variety of classification approaches into three major types 1. Instance based classifiers - Use observation directly (no models) - e.g. K

309 views • 28 slides

Chapter 6: Automatic Classification (Supervised Data Organization) 6.1 Simple Distance-based

Chapter 6: Automatic Classification (Supervised Data Organization) 6.1 Simple Distance-based Classifiers 6.2 Feature Selection 6.3 Distribution-based (Bayesian) Classifiers 6.4 Discriminative Classifiers: Decision Trees 6.5 Discriminative

626 views • 41 slides

System Introduction to Sensory Physiology: Sensory- Motor System General Properties of

System Introduction to Sensory Physiology: Sensory- Motor System General Properties of Sensory Systems 1. Importance of peripheral structures 3. Adequate Stimulus 5. Range Fractionation 7. Stimulus-Response

302 views • 26 slides

Data Dependence in Data Dependence in Combining Classifiers Combining Classifiers Mohamed

Data Dependence in Data Dependence in Combining Classifiers Combining Classifiers Mohamed Kamel, Nayer Wanas Mohamed Kamel, Nayer Wanas Pattern Analysis and Machine Intelligence Lab Pattern Analysis and Machine Intelligence Lab University of

690 views • 38 slides

Sensory Register More senses are better Some senses are stronger Link words to

MINDSIGHT The Eye of The Mind and Interpretation by Dr. Cary J. Goulard Sensory Register More senses are better Some senses are stronger Link words to sensory input Sensory analogies (feels like ) ( Retrieval ) Limited

613 views • 23 slides

Data Mining 2016 Bayesian Network Classifiers Ad Feelders Universiteit Utrecht Ad Feelders (

Data Mining 2016 Bayesian Network Classifiers Ad Feelders Universiteit Utrecht Ad Feelders ( Universiteit Utrecht ) Data Mining 1 / 48 Literature N. Friedman, D. Geiger and M. Goldszmidt Bayesian Network Classifiers Machine Learning, 29,

532 views • 49 slides

Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints

Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints Andrew Cotter 1 , Maya Gupta 1 , Heinrich Jiang 1 , Nathan Srebro 2 , Karthik Sridharan 3 , Serena Wang 1 , Blake Woodworth 2 , Seungil You 4 1 Google

103 views • 6 slides

Interpretation of Sensory Results Narinder Singh Sahni, Ph.D Schoof of Computational and

Sensory Methods and Interpretation of Sensory Results Narinder Singh Sahni, Ph.D Schoof of Computational and Integrative Sciences Jawaharlal Nehru University Topics for the day Sensory Evaluation-Taste, Experience and Chemistry

1.38k views • 78 slides

Automatically Evading Classifiers A Case Study on PDF Malware Classifiers Weilin Xu

Automatically Evading Classifiers A Case Study on PDF Malware Classifiers Weilin Xu David Evans Yanjun Qi University of Virginia Machine Learning is Solving Our Problems Fake Fake Spam IDS

1.07k views • 34 slides

PHGY 212 - Physiology SENSORY PHYSIOLOGY Sensory Neural Pathways Martin Par Assistant

PHGY 212 - Physiology SENSORY PHYSIOLOGY Sensory Neural Pathways Martin Par Assistant Professor of Physiology & Psychology pare@biomed.queensu.ca http://brain.phgy.queensu.ca/pare Pathways for Sensory Perception Pathways for Sensory

399 views • 26 slides