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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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4 results for “forgiveness”

Characterizing the Multiclass Learnability of Forgiving 0-1 Loss Functionscs.LG

Characterizes learnability of forgiving 0-1 loss functions in multiclass settings.

problem Understanding when multiclass learning with forgiving 0-1 loss functions is possible.

method Introduces a new combinatorial dimension based on Natarajan Dimension to determine learnability.

result A hypothesis class is learnable if and only if the Generalized Natarajan Dimension is finite.

multiclass learning forgiving loss Natarajan Dimension combinatorial dimension learnability

2025-10-09abs ↗pdf ↗

Decentralized Learning of Generative Adversarial Networks from Non-iid Datacs.LG

This work addresses a new problem that learns generative adversarial networks (GANs) from multiple data collections that are each i) owned separately by different clients and ii) drawn from a non-identical distribution that comprises different classes. Given such non-iid data as input, we aim to learn a distribution in…

2019-05-23abs ↗pdf ↗

Minimizing the Repayment Cost of Federal Student Loansq-fin.MF

Optimal student loan repayment strategies vary based on loan size.

problem Finding the most cost-effective repayment strategy for federal student loans.

method Analyzing the impact of different repayment strategies on total cost for varying loan sizes.

result Optimal repayment strategies depend on the loan balance, with different approaches for small, large, and intermediate balances.

student loans income-driven schemes forgiveness repayment cost fixed-rate debt

2022-07-07abs ↗pdf ↗

Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinementsstat.ML

New insights into stochastic methods for solving variational inequalities.

problem Understanding convergence behaviors of stochastic algorithms in variational inequalities.

method Re-casting SEG/SGDA as Markov Chains to analyze their probabilistic structures.

result The average iterate is asymptotically normal with a unique invariant distribution for various VIPs.

stochastic optimization variational inequalities Markov chains central limit theorem bias analysis

2023-06-28abs ↗pdf ↗