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    • A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD
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    • One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently
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    • Problems and Opportunities in Training Deep-Learning Software Systems: An Analysis of Variance
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    • DeepAntigen: a novel method for neoantigen prioritization via 3D genome and deep sparse learning
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    • On Minimax Optimality of GANs for Robust Mean Estimation
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    • Least-Squares Estimation of Weakly Convex Functions
    • A Penalized Regression Model for the Joint Estimation of eQTL Associations and Gene Network Structure
    • Multivariate Triangular Quantile Maps for Novelty Detection
    • Sum-of-squares Polynomial Flow
    • What Part of the Neural Network Does This? Understanding LSTMs by Measuring and Dissecting Neurons
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    • They Are Not Equally Reliable: Semantic Event Search using Differentiated Concept Classifiers
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    • Petuum: A New Platform for Distributed Machine Learning on Big Data
    • Linear Time Samplers for Supervised Topic Models using Compositional Proposals
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    • Minimizing Nonconvex Non-Separable Functions
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    • Better Approximation and Faster Algorithm Using the Proximal Average
    • Polar Operators for Structured Sparse Estimation
    • Characterizing the Representer Theorem
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    • A Polynomial-time Form of Robust Regression
    • Accelerated Training for Matrix-Norm Regularization: A Boosting Approach
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    • Analysis of Kernel Mean Matching under Covariate Shift
    • Regularizers versus Losses for Nonlinear Dimensionality Reduction
    • Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions
    • Distance Metric Learning by Minimal Distance Maximization
    • Rank/Norm Regularization with Closed-Form Solutions: Application to Subspace Clustering
    • Relaxed Clipping: A Global Training Method for Robust Regression and Classification
    • A Conditional Value-at-Risk Approach for Uncertain Markov Decision Processes
    • A General Projection Property for Distribution Families
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Breakneck

Breakneck

Dec 1, 2025·
Yaoliang Yu
Yaoliang Yu
· 1 min read
Table of Contents
    • To Read

By Dan Wang (Norton, 2025).

Withheld.

To Read

  • Derek Thompson and Ezra Klein (2025). Abundance. Avid Reader Press.
Last updated on Dec 1, 2025
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Yaoliang Yu
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Yaoliang Yu
← Finding Equilibrium Dec 21, 2025
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