🎪 Convex Optimization - pfh · Scour

Optimal payoff under Bregman-Wasserstein divergence constraints ⛰️Gradient Descent

Piece-wise linear isotonic regression 📊Empirical Bayes

Online Resource Allocation with Convex-set Machine-Learned Advice ⛰️Gradient Descent

Less-relevant results

How to fight the money stress ruins sleep and tanks productivity ⛰️Gradient Descent

fastcompany.com·21h

Global Convergence of Sampling-Based Nonconvex Optimization through Diffusion-Style Smoothing ⛰️Gradient Descent

Learning with Shallow Neural Networks on Cluster-Structured Features 🗺️Manifold Learning

Stochastic Mirror Descent under Iterate-Dependent Markov Noise: Analysis in the Asymptotic and Finite Time Regimes ⛰️Gradient Descent

Increasing Missingness to Reduce Bias: Richardson-SGD with Missing Data 📊Empirical Bayes

A Fourier perspective on the learning dynamics of neural networks: from sample complexities to mechanistic insights ⛰️Gradient Descent

Emergence of Frontier Superposition: M\"obius attractor and Cascade Supervision ⛰️Gradient Descent

Heuristic Pathologies and Further Variance Reduction via Uncertainty Propagation in the AIVAT Family of Techniques 📊Empirical Bayes

No Plan, Yet Human: A Reactive Robotics Model Predicts Human Planning Failures on a Clinical Task 🔗Markov Chains

DynMuon: A Dynamic Spectral Shaping View of Muon ⛰️Gradient Descent

Enabling Adversarial Robustness in AI Models through Kubeflow MLOps ⛰️Gradient Descent

Efficient Bilevel Optimization for Meta Label Correction in Noisy Label Learning 📦Pseudobulk

Sample efficient inductive matrix completion with noise and inexact side information 📐Matrix Factorization

Rethinking Neural Network Learning Rates: A Stackelberg Perspective ⛰️Gradient Descent

LWGR: Lagrangian-Constrained Personalized World Knowledge for Generative Recommendation 🔢Embeddings

Critic-Driven Voronoi-Quantization for Distilling Deep RL Policies to Explainable Models ⛰️Gradient Descent

Propagation of Chaos in Contextual Flow Maps 🗺️UMAP

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