machine learning – Page 20 – Andrew Fairless, Ph.D.

What I Read: Offline RL, Large Language Models

By Andrew Fairless on February 21, 2023December 16, 2022

https://sergeylevine.substack.com/p/offline-rl-and-large-language-models Offline RL and Large Language ModelsSergey LevineDec 4 “What if the purpose of a language model should not be to generate text at all, at least not directly? …Continue readingWhat I Read: Offline RL, Large Language Models

What I Read: Realtime ML

By Andrew Fairless on February 16, 2023December 16, 2022

https://fennel.ai/blog/seven-reasons-why-realtime-ml-is/ Seven Reasons Why Realtime ML Is Here To StayNikhil GargJune 17, 2022 “…more and more top tech companies are making a larger part of their machine learning as realtimeContinue readingWhat I Read: Realtime ML

What I Read: Biases, Saliency

By Andrew Fairless on February 9, 2023December 16, 2022

https://pair.withgoogle.com/explorables/saliency/ Searching for Unintended Biases With SaliencyAstrid Bertrand, Adam Pearce and Nithum ThainDecember 2022 “If there are spurious correlations in the training data, the model might develop unintended biases thatContinue readingWhat I Read: Biases, Saliency

What I Read: ML Observability

By Andrew Fairless on February 7, 2023December 4, 2022

https://medium.com/at-the-front-line/ml-observability-hype-or-here-to-stay-acef064ff843 ML Observability — Hype or Here to Stay?RuthOct 17 “Machine Learning Operations (MLOps) infrastructure is evolving at a phenomenal pace, and ML Observability is becoming a critical component ofContinue readingWhat I Read: ML Observability

What I Read: Causal Confounds, Sequential Decision

By Andrew Fairless on February 6, 2023December 4, 2022

https://blog.ml.cmu.edu/2022/11/28/causal-confounds-in-sequential-decision-making/ Causal Confounds in Sequential Decision MakingGokul SwamyNovember 28, 2022 “Using techniques from causal inference, we derive provably correct and scalable algorithms for sequential decision making in these sorts ofContinue readingWhat I Read: Causal Confounds, Sequential Decision

What I Read: Realtime ML Pipelines

By Andrew Fairless on February 1, 2023December 4, 2022

https://medium.com/@nparsons08/challenges-of-building-realtime-ml-pipelines-4782181425c7 Challenges of Building Realtime ML PipelinesNick ParsonsNov 18 “…as companies start introducing realtime into their ML pipelines, they are finding themselves having to weigh the trade-offs between performance, cost,Continue readingWhat I Read: Realtime ML Pipelines

What I Read: Machine Learning, Not Like Brain

By Andrew Fairless on January 31, 2023December 4, 2022

https://www.kdnuggets.com/2022/11/inescapable-conclusion-machine-learning-like-brain.html The Inescapable Conclusion: Machine Learning Is Not Like Your BrainBy Charles Simon, CEO of FutureAI on November 25, 2022 “The final article in this nine-part series summarizes the manyContinue readingWhat I Read: Machine Learning, Not Like Brain

What I Read: Matrix Multiplication

By Andrew Fairless on January 30, 2023December 4, 2022

https://www.quantamagazine.org/ai-reveals-new-possibilities-in-matrix-multiplication-20221123/ AI Reveals New Possibilities in Matrix MultiplicationBen BrubakerNovember 23, 2022 “Inspired by the results of a game-playing neural network, mathematicians have been making unexpected advances on an age-old mathContinue readingWhat I Read: Matrix Multiplication

What I Learn: video quality, neural networks

By Andrew Fairless on January 26, 2023December 4, 2022

https://netflixtechblog.com/for-your-eyes-only-improving-netflix-video-quality-with-neural-networks-5b8d032da09c For your eyes only: improving Netflix video quality with neural networksby Christos G. Bampis, Li-Heng Chen and Zhi LiNetflix Technology BlogNov 14 “Recently, we added another powerful tool toContinue readingWhat I Learn: video quality, neural networks

What I Learn: Preferences in Recommender Systems

By Andrew Fairless on January 23, 2023December 4, 2022

https://medium.com/understanding-recommenders/what-does-it-mean-to-give-someone-what-they-want-the-nature-of-preferences-in-recommender-systems-82b5a1559157 What Does it Mean to Give Someone What They Want? The Nature of Preferences in Recommender SystemsLuke Thorburn, Jonathan Stray, Priyanjana BenganiMar 11 “We’ll propose… concrete ways to buildContinue readingWhat I Learn: Preferences in Recommender Systems

Tag: machine learning