🤝 Open to Collab

Tahsin Rahit

rahit

1 3

https://tahsinrahit.com

AI & ML interests

Multimodal application in healthcare/oncology!

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updated a Space about 5 hours ago

rahit/repro-on-the-computational-complexity-of-performative-prediction

published a Space about 5 hours ago

rahit/repro-on-the-computational-complexity-of-performative-prediction

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rahit 's Spaces 40

Reproduction: On the Computational Complexity of Performative Prediction

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Reproduction: Dimension-Independent Convergence of Underdamped Langevin Monte Carlo in KL Divergence

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Reproduction: Floating-Point Networks with Automatic Differentiation Can Represent Almost All Floating-Point Functions and Their Gradients

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Reproduction: A Tight Theory of Error Feedback Algorithms in Distributed Optimization

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Reproduction: Task-Awareness Improves LLM Generations and Uncertainty

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Reproduction: Improved Dimension Dependence for Bandit Convex Optimization with Gradient Variation

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Reproduction: Accelerating Regression Tasks with Quantum Algorithms

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Reproduction: Provably Data-driven Lagrangian Relaxation for Mixed Integer Linear Programming

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Reproduction: Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function

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Reproduction: Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis

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Reproduction: The Implicit Bias of Adam and Muon on Smooth Homogeneous Neural Networks

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Reproduction: Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness, and Safety

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Reproduction: Beyond ReLU: Bifurcation, Oversmoothing, and Topological Priors

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Reproduction: Convergence Analysis of the Lion Optimizer in Centralized and Distributed Settings

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Reproduction: A Stronger Benchmark for Online Bilateral Trade: From Fixed Prices to Distributions

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Reproduction: The Interplay Between Interpolation and Aggregation in Regression: Optimal Sample Complexity

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Reproduction: Any-dimensional invariant universality

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Reproduction: On the Expressive Power of Permutation-Equivariant Weight-Space Networks

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Reproduction: On the Power of (Approximate) Reward Models for Inference-Time Scaling: Sequential Monte Carlo and Beyond

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Reproduction: Efficiently Learning Drifting Halfspaces with Massart Noise

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Reproduction: Understanding Behavior Cloning with Action Quantization

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