[6. Concentration Inequalities] 6.1 Markov and Chebyshev Inequalities
INTRODUCTION TO SCRATCH
MLSS 2012: G. Lugosi - Session 2: Concentration Inequalities in Machine Learning (Part 1)
mod02lec05 Azuma and McDiarmid inequalities
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Summary
यह व्याख्यान कंप्यूटेशनल न्यूरोसाइंस के सिद्धांतों का उपयोग करते हुए पावलोवियन कंडीशनिंग और सीखने की प्रक्रियाओं का विश्लेषण करता है। इसमें रिवॉर्ड प्रेडिक्शन एरर, टी.डी.-लर्निंग, और प्राइमेट मस्तिष्क में डोपामिनर्जिक कोशिकाओं की भूमिका की वैज्ञानिक व्याख्या की गई है, जो यह समझने में मदद करती है कि प्रत्याशा और वास्तविक परिणाम हमारे व्यवहार और खुशी को कैसे प्रभावित करते हैं। Concentration inequalities are one of the basic tools of probability and asymptotic geo- metric analysis, underlying the proofs of ... In the second video of Week 8, we begin our discussion of Concentration Inequalities. In particular, we cover: Chernoff Bounds, ... This series [Probability] closely follows Stanford University's CS 109 (Probability for Computer Scientists), and University of ... To access the translated content: 1. The translated content of this course is available in regional languages. For details please ... Machine Learning Summer School 2012: Session 2: Concentration Inequalities in Machine Learning (Part 1) - Gabor Lugosi ... Multiplicative family, Martingale method, bounded difference property.