#sample complexity
13 papers match
Tight Sample Complexity for Low-Rank Adaptation: Matching Bounds and Rank Selection
Arunan J
The paper derives matching upper and lower bounds on the sample complexity of low‑rank adaptation (LoRA) for fine‑tuning large models and provides a formal analysis of how to selec…
Actions Have Consequences: Detecting Outcome Performativity using Intervention Testing
Brandon Gower-Winter, Georg Krempl
The paper proposes a method called Outcome Performativity A/B Detection (OPAB) to identify when predictions causally affect the outcomes they forecast, by comparing outcome distrib…
Sample Complexity for the 2-Gromov-Wasserstein Distance
Pui Kuen Leung, Riku Okada, Samuel Lok-Hei Wong
The paper studies how many samples are needed for the empirical plug‑in estimator of the 2‑Gromov‑Wasserstein distance between compactly supported probability measures in Euclidean…
CASP: Learning-Augmented Offline Approximation with Verifiable Certificates and Bounded-Loss PAC Guarantees
Haifeng Li, Mo Hai
The paper proposes CASP, a learning-augmented framework that uses machine‑learned predictions to prune the search space of offline NP‑hard optimization problems, while a polynomial…
Quantum tomography for non-iid sources
Leonardo Zambrano
The paper proves that projected least‑squares quantum tomography retains optimal sample complexity even when the prepared states or channels are not independent and identically dis…
Entropy Equivalence Testing
Clément L. Canonne, Yash Pote, Jonathan Scarlett +1
The paper defines entropy equivalence testing, a relaxation of distribution closeness testing that distinguishes identical distributions from those whose Shannon entropies differ b…
The log log jam in Gaussian state tomography
Sitan Chen, Weiyuan Gong, Qi Ye +1
The paper proves that any tomography protocol using Gaussian measurements on continuous‑variable systems inevitably incurs a sample complexity that scales as log log E with the sys…
Testing the Independent Set Property in Hypergraphs
Elena Grigorescu, Shreya Nasa, Cameron Seth
The paper presents a new upper bound on the sample complexity for testing whether a q‑uniform hypergraph has an independent set of size ρn, improving previous results by reducing t…
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms
Miao Lu, Han Zhong, Tong Zhang +1
The paper studies reinforcement learning where the learner must be robust to differences between training and deployment environments, using interactive data collection and proposi…
Generalizing Preference-based Reinforcement Learning: a Rationality Model for Incomparability
Simone Drago, Marco Mussi, Leonardo Bianconi +1
The paper extends preference‑based reinforcement learning by allowing human experts to label trajectory pairs as incomparable, and introduces a Bradley‑Terry‑inspired rationality m…
From Expressivity to Sample Complexity: Narrow Teachers for Transformers via C-RASP
Michael Rizvi-Martel, Satwik Bhattamishra, Guillaume Rabusseau +1
The paper derives preliminary sample complexity bounds for learning C‑RASP constructions with Transformer models, linking their expressive power to learnability.
Optimal tomography of bosonic and fermionic Gaussian states
Senrui Chen, Marco Fanizza, Filippo Girardi +4
The paper determines the exact sample complexity for learning bosonic and fermionic Gaussian quantum states, showing that a number of copies scaling quadratically with the number o…
Learning and Testing Convex Functions
Renato Ferreira Pinto, Cassandra Marcussen, Elchanan Mossel +1
The paper investigates how to learn and test real-valued convex functions under the Gaussian distribution, providing algorithms with explicit sample‑complexity bounds assuming the…
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