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参考文献

研究集で引用した一次資料です。照合しやすいよう、題名と書誌情報は原文を保持しています。

全766件中 601–624件

Secure Single-Server Vector Aggregation with (Poly)Logarithmic Overhead
James Bell; K. A. Bonawitz; Adria Gascon; Tancrede Lepoint; Mariana Raykova
2020
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- A Sum without Its Summands: Secure Aggregation under Dropout and Collusion
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning
Jinhyun So; Ramy E. Ali; Basak Guler; Jiantao Jiao; Salman Avestimehr
2023
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- A Sum without Its Summands: Secure Aggregation under Dropout and Collusion
Segment Anything
, , , , , , , , , , ,
2023-04-05
参照箇所: Abstract; 原文方法、理论和实验章节见作者原始论文链接
確認範囲: 一手论文；原文研究归属原作者。本文的推导示例与建议实验方案另行标注，不冒充原论文或本站实测。
確認日: 2026-10-21
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- 多模态表征的可迁移性：对比目标、信息瓶颈与跨分布失效
- 可提示分割与视频记忆：SAM 接口、掩码歧义和跨域验证
Segregation of mitochondrial DNA heteroplasmy through a developmental genetic bottleneck in human embryos
Vasileios I. Floros; Angela Pyle; Sabine Dietmann; Wei Wei; Walfred C. W. Tang; Naoko Irie; Brendan Payne; Antonio Capalbo; Laila Noli; Jonathan Coxhead; Gavin Hudson; Moira Crosier; Henrik Strahl; Yacoub Khalaf; Mitinori Saitou; Dusko Ilic; M. Azim Surani; Patrick F. Chinnery
2018
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- Genomes within Cells: Drift, Selection and the Measurement of Mitochondrial Heteroplasmy
Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning
Zhu et al.
2023
参照箇所: Temporal-spatial DAS picker with pseudo-labels and phase association; sensor-domain distinction.
確認日: 2026-10-22
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- 从波形检测到地震目录：学习拾取、关联定位与完备性的联合分析
seL4: formal verification of an OS kernel
Gerwin Klein; Kevin Elphinstone; Gernot Heiser; June Andronick; David Cock; Philip Derrin; Dhammika Elkaduwe; Kai Engelhardt; Rafal Kolanski; Michael Norrish; Thomas Sewell; Harvey Tuch; Simon Winwood
2009
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- What a Verified System Actually Guarantees: Refinement and the Trusted Boundary
Selective organ targeting (SORT) nanoparticles for tissue-specific mRNA delivery and CRISPR–Cas gene editing
Qiang Cheng; Tuo Wei; Lukas Farbiak; Lindsay T. Johnson; Sean A. Dilliard; Daniel J. Siegwart
2020
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- Beyond Encapsulation: The Multistage Transport Problem of Messenger RNA Delivery
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Wang et al.
2022-03-21
参照箇所: v4 abstract
確認範囲: Samples multiple reasoning paths and marginalizes to choose a consistent answer. Correlated model errors can invalidate independent-vote intuitions.
確認日: 2026-10-15
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- 语言模型推理的验证边界：采样、搜索与正确性证据
Self-Consuming Generative Models Go MAD
Sina Alemohammad; Josue Casco-Rodriguez; Lorenzo Luzi; Ahmed Imtiaz Humayun; Hossein Babaei; Daniel LeJeune; Ali Siahkoohi; Richard G. Baraniuk
2023
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- Recursive Synthetic Data and the Fate of Rare Support
Self-Instruct: Aligning Language Models with Self-Generated Instructions
, , , , , ,
2022-12-20
参照箇所: Abstract; 原文方法、理论和实验章节见作者原始论文链接
確認範囲: 一手论文；原文研究归属原作者。本文的推导示例与建议实验方案另行标注，不冒充原论文或本站实测。
確認日: 2026-10-21
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- 合成训练数据的质量闭环：覆盖、筛选偏差与尾部信息流失
Self-Instruct: Aligning Language Models with Self-Generated Instructions
Yizhong Wang; Yeganeh Kordi; Swaroop Mishra; Alisa Liu; Noah A. Smith; Daniel Khashabi; Hannaneh Hajishirzi
2022
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- Recursive Synthetic Data and the Fate of Rare Support
Self-Paced Learning for Latent Variable Models
M. Pawan Kumar; Benjamin Packer; Daphne Koller
2010
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- A Curriculum Is Also a Sampling Policy
Self-training Improves Pre-training for Natural Language Understanding
Jingfei Du; Edouard Grave; Beliz Gunel; Vishrav Chaudhary; Onur Celebi; Michael Auli; Ves Stoyanov; Alexis Conneau
2020
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- Recursive Synthetic Data and the Fate of Rare Support
Semantics-Guided Synthesis
Jinwoo Kim; Qinheping Hu; Loris D'Antoni; Thomas Reps
2020
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- Programs from Counterexamples: Synthesis, Specifications, and Oracle Limits
SemDeDup: Data-efficient learning at web-scale through semantic deduplication
Amro Abbas; Kushal Tirumala; Dániel Simig; Surya Ganguli; Ari S. Morcos
2023
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- Data Multiplicity Is a Training Measure
Semi-Supervised Classification with Graph Convolutional Networks
,
2016-09-09
参照箇所: Abstract; 原文方法、理论和实验章节见作者原始论文链接
確認範囲: 一手论文；原文研究归属原作者。本文的推导示例与建议实验方案另行标注，不冒充原论文或本站实测。
確認日: 2026-10-21
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- 图神经网络的表达与传播：聚合可辨性、平滑和评估泄漏
Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf; Max Welling
2017
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- Graph Depth, Smoothing, and the Loss of Distinctions
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
Taku Kudo; John Richardson
2018
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- Tokens Are Not Units of Meaning: Probability Accounting Across Segmentations
Serializable snapshot isolation in PostgreSQL
Dan R. K. Ports; Kevin Grittner
2012
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- Serializable Transactions as an Invariant-Preservation Problem
Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider
Mohammad Shahrad; Rodrigo Fonseca; Inigo Goiri; Gohar Chaudhry; Paul Batum; Jason Cooke; Eduardo Laureano; Colby Tresness; Mark Russinovich; Ricardo Bianchini
2020
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- Serverless Is a Placement Decision: Cold Starts, Isolation, and State
SEV Secure Nested Paging Firmware ABI Specification
Advanced Micro Devices
2025
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- What an Attestation Establishes: Confidential Computing and the Remaining Trust Boundary
Shallow-Deep Networks: Understanding and Mitigating Network Overthinking
Yigitcan Kaya; Sanghyun Hong; Tudor Dumitras
2019
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- The Price of Stopping Early: Adaptive Depth, Confidence, and the Systems Cost of Neural Decisions
Sharp Minima Can Generalize For Deep Nets
Laurent Dinh; Razvan Pascanu; Samy Bengio; Yoshua Bengio
2017
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- The Same Predictor, a Sharper Minimum: Parameter Symmetry and the Meaning of Loss Geometry
Sharpness-Aware Minimization for Efficiently Improving Generalization
Pierre Foret; Ariel Kleiner; Hossein Mobahi; Behnam Neyshabur
2021
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- The Same Predictor, a Sharper Minimum: Parameter Symmetry and the Meaning of Loss Geometry

参考文献

Secure Single-Server Vector Aggregation with (Poly)Logarithmic Overhead

Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning

Segment Anything

Segregation of mitochondrial DNA heteroplasmy through a developmental genetic bottleneck in human embryos

Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning

seL4: formal verification of an OS kernel

Selective organ targeting (SORT) nanoparticles for tissue-specific mRNA delivery and CRISPR–Cas gene editing

Self-Consistency Improves Chain of Thought Reasoning in Language Models

Self-Consuming Generative Models Go MAD

Self-Instruct: Aligning Language Models with Self-Generated Instructions

Self-Instruct: Aligning Language Models with Self-Generated Instructions

Self-Paced Learning for Latent Variable Models

Self-training Improves Pre-training for Natural Language Understanding

Semantics-Guided Synthesis

SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Semi-Supervised Classification with Graph Convolutional Networks

Semi-Supervised Classification with Graph Convolutional Networks

SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing

Serializable snapshot isolation in PostgreSQL

Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider

SEV Secure Nested Paging Firmware ABI Specification

Shallow-Deep Networks: Understanding and Mitigating Network Overthinking

Sharp Minima Can Generalize For Deep Nets

Sharpness-Aware Minimization for Efficiently Improving Generalization