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351. Robot Perception and Learning
by Zhi Yan
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352. Robust Explainable Ai
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353. Minimum Gamma-Divergence for Regression and Classification Problems
by Shinto Eguchi
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354. Procedural Content Generation Via Machine Learning
by Matthew Guzdial; Sam Snodgrass; Adam Summerville
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355. Statistical Quantitative Methods in Finance
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356. Neural Networks With Tensorflow and Keras
by Philip Hua
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357. Domain-Informed Machine Learning for Smart Manufacturing
by Qiang Huang
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358. Mathematical Foundations of Reinforcement Learning
by Shiyu Zhao
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359. A Guide to Implementing Mlops
by Prafful Mishra
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360. Statistical Optimal Transport
by Sinho Chewi; Jonathan Niles-Weed; Philippe Rigollet
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361. Structured Representation Learning
by Yue Song; Thomas Anderson Keller; Nicu Sebe; Max Welling
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362. Tiny Machine Learning Quickstart
by Simone Salerno
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363. Deep Learning in Computational Mechanics
by Leon Herrmann; Moritz Jokeit; Oliver Weeger; Stefan Kollmannsberger
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364. Information Technologies and Mathematical Modelling. Queueing Theory and Related Fields
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365. A Guide to Implementing Mlops: From Data to Operations (Synthesis Lectures on Engineering, Science, and Technology)
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366. A Guide to Implementing Mlops: From Data to Operations (Synthesis Lectures on Engineering, Science, and Technology)
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367. A First Course in Statistical Learning
by Johannes Lederer
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368. Cross-Device Federated Recommendation
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