Resultados da busca - Valiant, Gregory

Matrix Multiplication in Quadratic Time and Energy? Towards a Fine-Grained Energy-Centric Church-Turing Thesis por Valiant, Gregory

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Stronger Calibration Lower Bounds via Sidestepping por Qiao, Mingda, Valiant, Gregory

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Exponential Weights Algorithms for Selective Learning por Qiao, Mingda, Valiant, Gregory

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Online Pen Testing por Qiao, Mingda, Valiant, Gregory

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Near-Optimal Mean Estimation with Unknown, Heteroskedastic Variances por Compton, Spencer, Valiant, Gregory

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Adaptive and oblivious statistical adversaries are equivalent por Blanc, Guy, Valiant, Gregory

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Attainability of Two-Point Testing Rates for Finite-Sample Location Estimation por Compton, Spencer, Valiant, Gregory

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Thompson Sampling Is 2-Competitive for Mistakes por Sellke, Mark, Valiant, Gregory

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Memory-Sample Tradeoffs for Linear Regression with Small Error por Sharan, Vatsal, Sidford, Aaron, Valiant, Gregory

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On Misspecification in Prediction Problems and Robustness via Improper Learning por Marsden, Annie, Duchi, John, Valiant, Gregory

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One-sided Matrix Completion from Two Observations Per Row por Cao, Steven, Liang, Percy, Valiant, Gregory

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A Generalized Trace Reconstruction Problem: Recovering a String of Probabilities por Rivkin, Joey, Valiant, Gregory, Valiant, Paul

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A Simple Geometric Proof of the Optimality of the Sequential Probability Ratio Test for Symmetric Bernoulli Hypotheses por Pabbaraju, Chirag, Valiant, Gregory, Verma, Rishi

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On the Entropy Calibration of Language Models por Cao, Steven, Valiant, Gregory, Liang, Percy

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Worst-Case Analysis for Randomly Collected Data por Chen, Justin Y., Valiant, Gregory, Valiant, Paul

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Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training por Tai, Kai Sheng, Bailis, Peter, Valiant, Gregory

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Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process por Blanc, Guy, Gupta, Neha, Valiant, Gregory, Valiant, Paul

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Sample Amplification: Increasing Dataset Size even when Learning is Impossible por Axelrod, Brian, Garg, Shivam, Sharan, Vatsal, Valiant, Gregory

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Efficient Convex Optimization Requires Superlinear Memory por Marsden, Annie, Sharan, Vatsal, Sidford, Aaron, Valiant, Gregory

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What Can Transformers Learn In-Context? A Case Study of Simple Function Classes por Garg, Shivam, Tsipras, Dimitris, Liang, Percy, Valiant, Gregory

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