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CSIAC Webinars - Cyber Security Game: A Model-based Game Theoretic Approach for Mitigating Cybersecurity Risk
⏲ 38 min 67 sec ✓ 20-Sep-2018
Minimax Algorithm in Game Playing | Artificial Intelligence
⏲ 12 minutes 29 seconds 👁 490.3K
Algorithms Explained – minimax and alpha-beta pruning
⏲ 11 minutes 1 second 👁 522.7K
Unique Ways to Cut and Peel Fruits & Vegetables!
⏲ 1:4:2 👁 17.8M
The Stag Hunt Game and Minimax Explained
⏲ 9 minutes 47 seconds 👁 6.3K
Decision Analysis 1: Maximax, Maximin, Minimax Regret
⏲ 4 minutes 44 seconds 👁 505.7K
Bleeding Money? Try a “Subscription Cleanse”
⏲ 0:44 👁 45.4M
(AGT1E5) [Game Theory] How to Solve for Maximin and Minimax Values in Zero-Sum Games
⏲ 12 minutes 17 seconds 👁 10.8K
Minimax Regret and EOL
⏲ 2 minutes 34 seconds 👁 20.5K
Active Learning, Drifting Distributions, and Convex Surrogate Losses - Liu Yang
⏲ 22 min 85 sec ✓ 15-May-2012
MINIMAX THEOREM informal illustration
⏲ 4 minutes 23 seconds 👁 1.9K
Game Theory maxmin Strategy
⏲ 5 minutes 41 seconds 👁 37.5K
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_csiac-webinars-cyber-security-game-a-model-based-game-theoretic-approach-for-mitigating-cybersecurity-risk.webp "https://www.csiac.org/podcast/cyber-security-game-a-model-based-game-theoretic-approach-for-mitigating-cybersecurity-risk/nnThis webinar describes the Cyber Security Game (CSG). CSG is a method that has been implemented in software that quantitatively identifies cyber security risks and uses this metric to determine the optimal employment of security methods for any given investment level. Cyber Security Game maximizes a system’s ability to operate in today’s contested cyber environment by m")
_minimax-algorithm-in-game-playing-124-artificial-intelligence.webp "Gate Smashers")
_algorithms-explained-minimax-and-alpha-beta-pruning.webp "Sebastian Lague")
_unique-ways-to-cut-and-peel-fruits-amp-vegetables.webp "Discover innovative techniques for cutting and peeling fruits and vegetables in our latest video tutorial! From creative slicing methods to unique peeling hacks, elevate your kitchen skills and impress your friends and family with your culinary creativity. We advise adult supervision and care at all times. This video is made for entertainment purposes. We do not make any warranties about the completeness, safety and reliability. Any action you take upon the information on this video is strictly at your own risk, and we will not be liable for any damages or losses. It is the viewer's responsibility to use judgment, care and precautions if one plans to replicate. <br/><br/>The following video might feature activity performed by our actors within controlled environment- please use judgment, care, and precaution if you plan to replicate. <br/><br/>All product and company names shown in the video are trademarks™️ or registered®️ trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them. <br/><br/>------------------------------------------------------------------------------------ <br/><br/>▶️ TheSoul Music: https://www.music.thesoul-publishing.com <br/>◉ Our Spotify: https://sptfy.com/TheSoulMusic <br/>◉ TikTok: https://www.tiktok.com/@thesoul.music <br/>◉ YouTube:/ @thesoulsound<br/><br/>◉ 5-Minute Crafts:/ @5minutecraftsyoutube <br/>◉ 5-Minute Crafts DIY: / @5minutecraftsdiy <br/>◉ 5-Minute Crafts PLAY: / @5minutecraftsplay <br/><br/>◉ Music by Epidemic Sound: https://www.epidemicsound.com/")
_the-stag-hunt-game-and-minimax-explained.webp "Ashley Hodgson")
_decision-analysis-1-maximax-maximin-minimax-regret.webp "Joshua Emmanuel")
_bleeding-money-try-a-subscription-cleanse.webp "A “subscription cleanse” is one method that financial experts recommend to avoid losing money to unnecessary recurring payments. Buzz60’s Matt Hoffman reports.")
_agt1e5-game-theory-how-to-solve-for-maximin-and-minimax-values-in-zero-sum-games.webp "selcuk ozyurt")
_minimax-regret-and-eol.webp "Raihana Zainordin")
_active-learning-drifting-distributions-and-convex-surrogate-losses-liu-yang.webp "We study the problem of active learning in a stream-based setting, allowing the distribution of the examples to change over time. We prove upper bounds on the number of prediction mistakes and number of label requests for established disagreement-based active learning algorithms, both in the realizable case and under Tsybakov noise. We further prove minimax lower bounds for this problem.nnIt is often computationally hard to run these methods with the 0-1 loss. Passive learning often resolves thi")
_minimax-theorem-informal-illustration.webp "Sanjoy Das")
_game-theory-maxmin-strategy.webp "José Vidal")
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