1 √2logn √ 2 , ( 2) logn , 2 CSCI 570 – Spring 2021 – HW 1 Rubric Due Feb 07 logn 3 n2 2n , nlogn, n(logn) , 2 , 2 [Rubic (10 points) The grader will try to find the longest common subse- quence between the student’s solution and our solution. The […]
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EECS-4412: Data Mining Frequent Pattern & Association Rule Mining Parke Godfrey (Thanks to Aijun An & Jiawei Han) Outline Basic concepts of association rule learning Apriori algorithm FP-Growth Algorithm Finding interesting rules. 2 Why Mining Association Rules? Objective: Finding interesting co-occurring items (or objects, events) in a given data set. Examples: Given a database of
2/25/2021 OneNote Algorithms for CFLs Thursday, February 25, 2021 11:41 AM https://mcgill-my.sharepoint.com/personal/prakash_panangaden_mcgill_ca/_layouts/15/Doc.aspx?sourcedoc={4ebabb6a-e289-462f-821b-913836894465}&action=e… 1/6 2/25/2021 OneNote https://mcgill-my.sharepoint.com/personal/prakash_panangaden_mcgill_ca/_layouts/15/Doc.aspx?sourcedoc={4ebabb6a-e289-462f-821b-913836894465}&action=e… 2/6 2/25/2021 OneNote https://mcgill-my.sharepoint.com/personal/prakash_panangaden_mcgill_ca/_layouts/15/Doc.aspx?sourcedoc={4ebabb6a-e289-462f-821b-913836894465}&action=e… 3/6 2/25/2021 OneNote https://mcgill-my.sharepoint.com/personal/prakash_panangaden_mcgill_ca/_layouts/15/Doc.aspx?sourcedoc={4ebabb6a-e289-462f-821b-913836894465}&action=e… 4/6 2/25/2021 OneNote https://mcgill-my.sharepoint.com/personal/prakash_panangaden_mcgill_ca/_layouts/15/Doc.aspx?sourcedoc={4ebabb6a-e289-462f-821b-913836894465}&action=e… 5/6 2/25/2021 OneNote https://mcgill-my.sharepoint.com/personal/prakash_panangaden_mcgill_ca/_layouts/15/Doc.aspx?sourcedoc={4ebabb6a-e289-462f-821b-913836894465}&action=e… 6/6
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Algorithms for CFLs Thursday, February 25, 2021 11:41 AM
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CSCI 570 – Spring 2021 – HW 2 Due Sunday Feb. 22 (by 4:00 AM) Problem 1 (20 points) Suppose you are given two sets A and B, each containing n positive integers. You can choose to reorder each set however you like. After reordering, let ai be the i-th element of set A, and
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COMP5329 – Deep Learning¶ Tutorial 2 – Multilayer Neural Network¶ Semester 1, 2021 Objectives: • To understand the multi-layer perceptron. • To become familiar with backpropagation. Instructions: • Go to File->Open. Drag and drop “lab2MLP_student.ipynb” file to the home interface and click upload. • Read the code and complete the exercises. • To run the
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Agent-based Systems Paolo Turrini www.dcs.warwick.ac.uk/~pturrini R p.turrini@warwick.ac.uk Markov Decision Processes Policies are strategies Paolo Turrini Policies Agent-based Systems Plan for Today We now go back to a ”typical” AI framework: Markov Decision Processes Plans and policies Optimal policies These are ”one player” games with perfect information. Except they are not played on trees. This
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3/12/2021 1 CS 118 Discussion Week 10: Mobility and Security Slides by Eric Newberry, UCLA Winter 2021 Reminders and Announcements • Project 2 and Homework 4 are due at 11:59pm today! • Please turn something in for partial credit even if it doesn’t check every box! • “Triage” your remaining time – get regular forwarding
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3/5/2021 1 CS 118 Discussion Week 9: The Link Layer and Wireless Questions • Any questions from last week’s material or Project 2? 3/5/2021 2 Ethernet Switches • Link Layer • store, forward Ethernet frames • examine incoming frame’s MAC address, selectively forward frame to one-or- more outgoing links when frame is to be forwarded
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Agent-based Systems Paolo Turrini www.dcs.warwick.ac.uk/~pturrini R p.turrini@warwick.ac.uk Multi-agent Learning Paolo Turrini Learning and Population Dynamics Agent-based Systems In this lecture We are going to look at Markov Decision Processes with many agents: The idea is that agents interact repeatedly and learn each others’ strategies Connection with game theory Revisiting learning as evolutionary process A
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