参考来源

第 481–504 条，共 766 条来源

481. OAuth 2.0 Token Introspection

     Justin Richer
     2015
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     • Permission Has a Time: Relationship-Based Authorization and Consistent Revocation

482. OAuth 2.0 Token Revocation

     Torsten Lodderstedt; Stefanie Dronia; Marius Scurtescu
     2013
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     • Permission Has a Time: Relationship-Based Authorization and Consistent Revocation

483. ObliviStore: High Performance Oblivious Distributed Cloud Data Store - Extended Abstract

     Emil Stefanov; Elaine Shi
     2013
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     • Hiding the Address: Oblivious RAM, Leakage, and the Cost of Access Privacy

484. Observation of high-energy neutrinos from the Galactic plane

     IceCube Collaboration*†; R. Abbasi; M. Ackermann; J. Adams; J. A. Aguilar; M. Ahlers; et al.
     2023-06-30

     来源定位: Abstract; diffuse-template likelihood

     核查范围: 银河面弥散统计证据，不等于逐个源定位。

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     • 一条粒子轨迹指向哪里：中微子来源、多信使关联与全局显著性

485. Observation of spatial charge and spin correlations in the 2D Fermi-Hubbard model

     Lawrence W. Cheuk; Matthew A. Nichols; Katherine R. Lawrence; Melih Okan; Hao Zhang; Ehsan Khatami; Nandini Trivedi; Thereza Paiva; Marcos Rigol; Martin W. Zwierlein
     2016
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     • Learning from an Artificial Lattice: What Fermi-Hubbard Quantum Simulators Actually Measure

486. Observation-based early-warning signals for a collapse of the Atlantic Meridional Overturning Circulation

     Niklas Boers
     2021
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     • Reading an Ocean Circulation: AMOC Observations, Proxy Ambiguity and Early-Warning Claims

487. Off-Policy Deep Reinforcement Learning without Exploration

     Scott Fujimoto; David Meger; Doina Precup
     2019
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     • The Action Missing from the Dataset: Support, Pessimism, and Identification in Offline Deep Reinforcement Learning

488. Offline Reinforcement Learning with Implicit Q-Learning

     Ilya Kostrikov; Ashvin Nair; Sergey Levine
     2021
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     • The Action Missing from the Dataset: Support, Pessimism, and Identification in Offline Deep Reinforcement Learning

489. Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

     Sergey Levine; Aviral Kumar; George Tucker; Justin Fu
     2020
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     • The Action Missing from the Dataset: Support, Pessimism, and Identification in Offline Deep Reinforcement Learning

490. On Calibration of Modern Neural Networks

     Chuan Guo; Geoff Pleiss; Yu Sun; Kilian Q. Weinberger
     2017
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     • Calibrated Probabilities Are Not Yet Good Decisions

491. On Degeneracies in Retrievals of Exoplanetary Transmission Spectra

     Luis Welbanks; Nikku Madhusudhan
     2019
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     • An Atmosphere through a Spectrum: Clouds, Stellar Contamination and Exoplanet Retrieval

492. On instabilities of deep learning in image reconstruction and the potential costs of AI

     Vegard Antun; Francesco Renna; Clarice Poon; Ben Adcock; Anders C. Hansen
     2020
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     • A Plausible Image Is Not a Measurement: Learned MRI Reconstruction and Data Consistency

493. On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

     Nitish Shirish Keskar; Dheevatsa Mudigere; Jorge Nocedal; Mikhail Smelyanskiy; Ping Tak Peter Tang
     2017
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     • The Same Predictor, a Sharper Minimum: Parameter Symmetry and the Meaning of Loss Geometry

494. On Lazy Training in Differentiable Programming

     Lénaïc Chizat; Edouard Oyallon; Francis Bach
     2019
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     • Beyond a Frozen Tangent: What Kernel Limits Explain about Neural Feature Learning

495. On the Bottleneck of Graph Neural Networks and its Practical Implications

     Uri Alon; Eran Yahav
     2021
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     • Graph Depth, Smoothing, and the Loss of Distinctions

496. On the detection of a cosmic dawn signal in the radio background

     Saurabh Singh; Jishnu Nambissan T.; Ravi Subrahmanyan; N. Udaya Shankar; B. S. Girish; A. Raghunathan; R. Somashekar; K. S. Srivani; Mayuri Sathyanarayana Rao
     2022
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     • Listening beneath the Foreground: Calibration and Identifiability in Cosmic-Dawn Radio Experiments

497. On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport

     Lénaïc Chizat; Francis Bach
     2018
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     • Beyond a Frozen Tangent: What Kernel Limits Explain about Neural Feature Learning

498. On the Limitations of Multimodal VAEs

     Imant Daunhawer; Thomas M. Sutter; Kieran Chin-Cheong; Emanuele Palumbo; Julia E. Vogt
     2021
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     • When a Sensor Is Missing: Multimodal Learning and Identifiability

499. On the Locality of Codeword Symbols

     Parikshit Gopalan; Cheng Huang; Huseyin Simitci; Sergey Yekhanin
     2012
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     • Erasure Coding in Real Storage Systems: Durability, Locality, and Repair Traffic

500. On The Power of Curriculum Learning in Training Deep Networks

     Guy Hacohen; Daphna Weinshall
     2019
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     • A Curriculum Is Also a Sampling Policy

501. On the Size of Pairing-Based Non-interactive Arguments

     Jens Groth
     2016
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     • Succinct Proofs, Substantial Costs: Evaluating Zero-Knowledge Systems End to End

502. On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes

     Rishabh Agarwal; Nino Vieillard; Yongchao Zhou; Piotr Stanczyk; Sabela Ramos; Matthieu Geist; Olivier Bachem
     2023
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     • Recursive Synthetic Data and the Fate of Rare Support

503. One-step Diffusion with Distribution Matching Distillation

     Tianwei Yin; Michaël Gharbi; Richard Zhang; Eli Shechtman; Fredo Durand; William T. Freeman; Taesung Park
     2024
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     • One Step Is a Budget, Not a Distribution: Consistency Models and the Evidence for Fast Generation

504. Optimizing and Evaluating Transient Gradual Typing

     Michael M. Vitousek; Jeremy G. Siek; Avik Chaudhuri
     2019
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     • Types at the Boundary: Gradual Guarantees, Blame, and the Cost of Enforcement