RyeCatcher (Justin Johnson)

Reproduction: Compact Conformal Subgraphs

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Reproduction: Maximin Relative Improvement: Fair Learning as a Bargaining Problem

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Reproduction: Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels

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Reproduction: The Catastrophic Failure of the k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It

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Reproduction: Asymptotically Optimal Sequential Testing with Markovian Data

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Reproduction: Two-Layer Linear Auto-Regressive Models Estimate Latent States

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Reproduction: Stability and Generalization of Nonconvex Optimization with Heavy-Tailed Noise

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Reproduction: Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks

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Reproduction: Next-Token Prediction and Regret Minimization

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Reproduction: Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?

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Reproduction: Mirror Descent Under Generalized Smoothness

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Reproduction: Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible?

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Reproduction: Linear Regression with Unknown Truncation Beyond Gaussian Features

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Reproduction: Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment

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Reproduction: Certificate-Guided Pruning for Stochastic Lipschitz Optimization

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Reproduction: Bregman meets Lévy: Stochastic Mirror Descent with Heavy-Tailed Noise in Continuous and Discrete Time

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Reproduction: Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning

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Reproduction: Exactly Computing do-Shapley Values

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Reproduction: Revenue Guarantees of No-Swap-Regret Dynamics in First Price Auctions

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Reproduction: Innovation: An Almost Characterization of Hallucination

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Reproduction: Solving Stochastic Variational Inequalities without the Bounded Variance Assumption

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Reproduction: Second-Order Bilevel Optimization with Accelerated Convergence Rates

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Reproduction: Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality

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Reproduction: Rationality Measurement and Theory for Reinforcement Learning Agents

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Justin Johnson

AI & ML interests

Organizations

RyeCatcher 's Spaces 163

Reproduction: Compact Conformal Subgraphs

Reproduction: Maximin Relative Improvement: Fair Learning as a Bargaining Problem

Reproduction: Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels

Reproduction: The Catastrophic Failure of the k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It

Reproduction: Asymptotically Optimal Sequential Testing with Markovian Data

Reproduction: Two-Layer Linear Auto-Regressive Models Estimate Latent States

Reproduction: Stability and Generalization of Nonconvex Optimization with Heavy-Tailed Noise

Reproduction: Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks

Reproduction: Next-Token Prediction and Regret Minimization

Reproduction: Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?

Reproduction: Mirror Descent Under Generalized Smoothness

Reproduction: Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible?

Reproduction: Linear Regression with Unknown Truncation Beyond Gaussian Features

Reproduction: Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment

Reproduction: Certificate-Guided Pruning for Stochastic Lipschitz Optimization

Reproduction: Bregman meets Lévy: Stochastic Mirror Descent with Heavy-Tailed Noise in Continuous and Discrete Time

Reproduction: Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning

Reproduction: Exactly Computing do-Shapley Values

Reproduction: Revenue Guarantees of No-Swap-Regret Dynamics in First Price Auctions

Reproduction: Innovation: An Almost Characterization of Hallucination

Reproduction: Solving Stochastic Variational Inequalities without the Bounded Variance Assumption

Reproduction: Second-Order Bilevel Optimization with Accelerated Convergence Rates

Reproduction: Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality

Reproduction: Rationality Measurement and Theory for Reinforcement Learning Agents

Justin Johnson

AI & ML interests

Organizations

RyeCatcher 's Spaces 163 Sort: Recently updated

Reproduction: Compact Conformal Subgraphs

Reproduction: Maximin Relative Improvement: Fair Learning as a Bargaining Problem

Reproduction: Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels

Reproduction: The Catastrophic Failure of *the* k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It

Reproduction: Asymptotically Optimal Sequential Testing with Markovian Data

Reproduction: Two-Layer Linear Auto-Regressive Models Estimate Latent States

Reproduction: Stability and Generalization of Nonconvex Optimization with Heavy-Tailed Noise

Reproduction: Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks

Reproduction: Next-Token Prediction and Regret Minimization

Reproduction: Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?

Reproduction: Mirror Descent Under Generalized Smoothness

Reproduction: Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible?

Reproduction: Linear Regression with Unknown Truncation Beyond Gaussian Features

Reproduction: Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment

Reproduction: Certificate-Guided Pruning for Stochastic Lipschitz Optimization

Reproduction: Bregman meets Lévy: Stochastic Mirror Descent with Heavy-Tailed Noise in Continuous and Discrete Time

Reproduction: Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning

Reproduction: Exactly Computing do-Shapley Values

Reproduction: Revenue Guarantees of No-Swap-Regret Dynamics in First Price Auctions

Reproduction: Innovation: An Almost Characterization of Hallucination

Reproduction: Solving Stochastic Variational Inequalities without the Bounded Variance Assumption

Reproduction: Second-Order Bilevel Optimization with Accelerated Convergence Rates

Reproduction: Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality

Reproduction: Rationality Measurement and Theory for Reinforcement Learning Agents

RyeCatcher 's Spaces 163

Reproduction: The Catastrophic Failure of the k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It