PPT-Accountability in Machine Learning Systems via Program Analysis

Author : brantley | Published Date : 2024-11-16

Learning Systems via Program Analysis Gihyuk Ko PhD Candidate Department of Electrical and Computer Engineering Carnegie Mellon University slides were borrowed

Presentation Embed Code

Download Presentation

Download Presentation The PPT/PDF document "Accountability in Machine Learning Syste..." is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Accountability in Machine Learning Systems via Program Analysis: Transcript

Learning Systems via Program Analysis Gihyuk Ko PhD Candidate Department of Electrical and Computer Engineering Carnegie Mellon University slides were borrowed and modified from Anupam . Gordon Machine Learning Department Carnegie Mellon University Pittsburgh Pennsylvania 15213 Abstract Recently a number of researchers have proposed spectral algorithms for learning models of dynam ical systemsfor example Hidden Markov Models HMMs Pa Stanford University. Learning. . to improve our lives. Input. Computers Can Learn?. Computers can learn to . predict. Computers can learn to . act. Output. Program. Parameters. Learned to get desired input/output mapping. By Namita Dave. Overview. What are compiler optimizations?. Challenges with optimizations. Current Solutions. Machine learning techniques. Structure of Adaptive compilers. Introduction. O. ptimization . Massimo . Poesio. INTRO TO MACHINE LEARNING. WHAT IS LEARNING. Memorizing something . Learning facts through observation and exploration . Developing motor and/or cognitive skills through practice . Organizing new knowledge into general, effective representations . . Understanding the disconnect between resources . and . results. Nic Spaull. UJ – . Kagiso. Trust Education Conversation – 1 October 2013. Outline. Brief overview of spending in SA. Motivations for increasing resources. Adapting a Program Analysis . via Bayesian Optimisation. b. y Hakjoo Oh, Hongseok Yang and Kwangkeun Yi. OOPSLA 2015. . Research Topics in Software Engineering. Maximilian Wurm. Motivation. 2. *. Appeared . Dan Roth. University of Illinois, Urbana-Champaign. danr@illinois.edu. http://L2R.cs.uiuc.edu/~danr. 3322 SC. 1. CS446: Machine Learning. Tuesday, Thursday: . 17:00pm-18:15pm . 1404 SC. . Office hours: . Prabhat. Data Day. August 22, 2016. Roadmap. Why you should care about Machine Learning?. Trends in Industry. Trends in Science . What is Machine Learning?. Taxonomy. Methods. Tools (Evan . Racah. ). 1. LESSON OUTCOME:. This lesson provides an overview of doctrinal responsibilities, philosophies, and objectives for . applying HR Metrics in they day to day operations. . At the conclusion of this block of instruction, students will be able to . Increasingly Autonomous TechnologiesArtificial Intelligenceaprimer for CCW delegatesUNIDIR RESOURCESNo 8AcknowledgementsSupport from UNIDIRs core funders provides the foundation for all of the Institu Dangers and Opportunities. Davide Faranda . CNRS – LSCE. M. Vrac, P. . Yiou. , F.M.E. Pons, A. . Hamid, G. . . Carella. , . C.G. . Ngoungue. . Langue, S. . Thao, V. . Gautard. IN2P3-IRFU. Context. The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand Gihyuk Ko. PhD Student, Department of Electrical and Computer Engineering. Carnegie Mellon University. November. 14, 2016. *some slides were borrowed from . Anupam. . Datta’s. MIT Big . Data@CSAIL. Ryan Ma . Background and Purpose of the Project. Aerodynamic analysis is one of the most crucial traits of a vehicle. It affects the fuel consumption of a car. . The shape of the car significantly affects the aerodynamic performances, which includes the lift and the drag. .

Download Document

Here is the link to download the presentation.
"Accountability in Machine Learning Systems via Program Analysis"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.