🔍 We introduces a nontrivial two-layer linear network with 2D input, where one dimension is relevant to the response and the other is irrelevant. Such an input structure reveals new insights about the EoS phenomenon. (2/3) #MachineLearningTheory

Bias-variance tradeoff is a fundamental concept in ML. Bias refers to error from overly simplistic models, while variance refers to error from overly complex models. Balancing these errors helps create models that generalize well to new data. #MachineLearningTheory

Machine Learning in Theory vs. Real-World.🙄 #machinelearningtheory #realworldapplication

Why #Poetry is a variety of #Mathematical experience #MachineLearningTheory is shedding new light on how to think about the mysterious and ineffable nature of #Art "To think a lot but all at once, we have to think associatively, self-referentially, vividly, temporally"…

60 students are attending our 1st in-person #machinelearningtheory summer school this week. Organizer @BorisHanin, assistant prof of operations research & financial engineering, aims to promote "a common language" to connect the next gen. of researchers in the field.

I can't stop reading @danintheory et al.'s fantastic book! Building some tools for #machinelearningtheory calculations along the way.

RT When Is Bayesian Machine Learning Actually Useful? dlvr.it/SHzvDF #machinelearningtheory #bayesianmachinelearning

RT Theory of learning — a Bayesian perspective of generalization dlvr.it/S51r6k #machinelearningtheory #pacbayes #bayesianmachinelearning

Know the basic theory behind machine learning and also use python to digest it in. You can visit this website python-course.eu/machine_learni… I found it useful. #Python #MachineLearning #MachineLearningTheory

Some great notes on convex scoring rule function in a multi-agent for learning #gametheory #machinelearningtheory #submodularity