DIT: Dimension Reduction View on Optimal NFT Rarity Meters
Fuente:
arXiv
Guardado en:
| Autores principales: | Belousov, Dmitry, Yanovich, Yury |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Detecting Rug Pulls in Decentralized Exchanges: Machine Learning Evidence from the TON Blockchain
por: Yaremus, Dmitry, et al.
Publicado: (2025)
por: Yaremus, Dmitry, et al.
Publicado: (2025)
The Origins of MEV: Systematic Attribution of Arbitrage Opportunity Creation at Scale
por: Seoev, Andrei, et al.
Publicado: (2026)
por: Seoev, Andrei, et al.
Publicado: (2026)
SwarmRaft: Leveraging Consensus for Robust Drone Swarm Coordination in GNSS-Degraded Environments
por: Dev, Kapel, et al.
Publicado: (2025)
por: Dev, Kapel, et al.
Publicado: (2025)
Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction
por: Demidovich, Yury, et al.
Publicado: (2024)
por: Demidovich, Yury, et al.
Publicado: (2024)
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
por: Li, Zhe, et al.
Publicado: (2024)
por: Li, Zhe, et al.
Publicado: (2024)
Federated Incomplete Multi-View Clustering with Heterogeneous Graph Neural Networks
por: Yan, Xueming, et al.
Publicado: (2024)
por: Yan, Xueming, et al.
Publicado: (2024)
Learning to Shard: RL for Co-optimizing the Parallelism Degrees and Per-operator Sharding Dimensions in Distributed LLM Inference
por: Yin, Ruokai, et al.
Publicado: (2025)
por: Yin, Ruokai, et al.
Publicado: (2025)
Kareus: Joint Reduction of Dynamic and Static Energy in Large Model Training
por: Wu, Ruofan, et al.
Publicado: (2026)
por: Wu, Ruofan, et al.
Publicado: (2026)
FedMSGL: A Self-Expressive Hypergraph Based Federated Multi-View Learning
por: Li, Daoyuan, et al.
Publicado: (2025)
por: Li, Daoyuan, et al.
Publicado: (2025)
Optimal Batch Allocation for Wireless Federated Learning
por: Song, Jaeyoung, et al.
Publicado: (2024)
por: Song, Jaeyoung, et al.
Publicado: (2024)
Unpacking Maximum Extractable Value on Polygon: A Study on Atomic Arbitrage
por: Vostrikov, Daniil, et al.
Publicado: (2025)
por: Vostrikov, Daniil, et al.
Publicado: (2025)
Communication-Efficient Federated Learning by Quantized Variance Reduction for Heterogeneous Wireless Edge Networks
por: Wang, Shuai, et al.
Publicado: (2025)
por: Wang, Shuai, et al.
Publicado: (2025)
Optimal Scheduling Algorithms for LLM Inference: Theory and Practice
por: Bari, Agrim, et al.
Publicado: (2025)
por: Bari, Agrim, et al.
Publicado: (2025)
Deterministic Bounds in Committee Selection: Enhancing Decentralization and Scalability in Distributed Ledgers
por: Melnikov, Grigorii, et al.
Publicado: (2024)
por: Melnikov, Grigorii, et al.
Publicado: (2024)
Personalized Federated Heat-Kernel Enhanced Multi-View Clustering via Advanced Tensor Decomposition Techniques
por: Sinaga, Kristina P.
Publicado: (2025)
por: Sinaga, Kristina P.
Publicado: (2025)
GeoT: Tensor Centric Library for Graph Neural Network via Efficient Segment Reduction on GPU
por: Yu, Zhongming, et al.
Publicado: (2024)
por: Yu, Zhongming, et al.
Publicado: (2024)
Optimizing the Optimal Weighted Average: Efficient Distributed Sparse Classification
por: Lu, Fred, et al.
Publicado: (2024)
por: Lu, Fred, et al.
Publicado: (2024)
Learning the Optimal Path and DNN Partition for Collaborative Edge Inference
por: Huang, Yin, et al.
Publicado: (2024)
por: Huang, Yin, et al.
Publicado: (2024)
FedAdaVR: Adaptive Variance Reduction for Robust Federated Learning under Limited Client Participation
por: Howlader, S M Ruhul Kabir, et al.
Publicado: (2026)
por: Howlader, S M Ruhul Kabir, et al.
Publicado: (2026)
Optimal Routing for Federated Learning over Dynamic Satellite Networks: Tractable or Not?
por: Zhao, Yi, et al.
Publicado: (2026)
por: Zhao, Yi, et al.
Publicado: (2026)
Preserving Near-Optimal Gradient Sparsification Cost for Scalable Distributed Deep Learning
por: Yoon, Daegun, et al.
Publicado: (2024)
por: Yoon, Daegun, et al.
Publicado: (2024)
CDFGNN: a Systematic Design of Cache-based Distributed Full-Batch Graph Neural Network Training with Communication Reduction
por: Zhang, Shuai, et al.
Publicado: (2024)
por: Zhang, Shuai, et al.
Publicado: (2024)
Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design
por: Yue, Xubo, et al.
Publicado: (2023)
por: Yue, Xubo, et al.
Publicado: (2023)
Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness
por: Pavlovic, Nikola, et al.
Publicado: (2024)
por: Pavlovic, Nikola, et al.
Publicado: (2024)
Near-Optimal Resilient Aggregation Rules for Distributed Learning Using 1-Center and 1-Mean Clustering with Outliers
por: Yi, Yuhao, et al.
Publicado: (2023)
por: Yi, Yuhao, et al.
Publicado: (2023)
FaasMeter: Energy-First Serverless Computing
por: Rehman, Abdul, et al.
Publicado: (2024)
por: Rehman, Abdul, et al.
Publicado: (2024)
BestServe: Serving Strategies with Optimal Goodput in Collocation and Disaggregation Architectures
por: Hu, Xiannan, et al.
Publicado: (2025)
por: Hu, Xiannan, et al.
Publicado: (2025)
Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data Similarity
por: Bylinkin, Dmitry, et al.
Publicado: (2024)
por: Bylinkin, Dmitry, et al.
Publicado: (2024)
Optimal Broadcast Schedules in Logarithmic Time with Applications to Broadcast, All-Broadcast, Reduction and All-Reduction
por: Träff, Jesper Larsson
Publicado: (2024)
por: Träff, Jesper Larsson
Publicado: (2024)
Near-Optimal Privacy-Preserving Learning for Max-Min Fair Multi-Agent Bandits
por: Leshem, Amir
Publicado: (2023)
por: Leshem, Amir
Publicado: (2023)
Dynamic Fee for Reducing Impermanent Loss in Decentralized Exchanges
por: Lebedeva, Irina, et al.
Publicado: (2025)
por: Lebedeva, Irina, et al.
Publicado: (2025)
From Impermanent Loss to Sustainable Gain: Quantifying Profitability Zones for Liquidity Providers on DEX
por: Melnikov, Ignat, et al.
Publicado: (2026)
por: Melnikov, Ignat, et al.
Publicado: (2026)
Characterizing Path-Independent Fees: A Route to Zero Impermanent Loss in CPMMs
por: Voronin, Andrey, et al.
Publicado: (2026)
por: Voronin, Andrey, et al.
Publicado: (2026)
SMoFi: Step-wise Momentum Fusion for Split Federated Learning on Heterogeneous Data
por: Yang, Mingkun, et al.
Publicado: (2025)
por: Yang, Mingkun, et al.
Publicado: (2025)
Incentivizing Permissionless Distributed Learning of LLMs
por: Lidin, Joel, et al.
Publicado: (2025)
por: Lidin, Joel, et al.
Publicado: (2025)
SwiftSpec: Ultra-Low Latency LLM Decoding by Scaling Asynchronous Speculative Decoding
por: Zhang, Ziyi, et al.
Publicado: (2025)
por: Zhang, Ziyi, et al.
Publicado: (2025)
FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA
por: Jhunjhunwala, Divyansh, et al.
Publicado: (2025)
por: Jhunjhunwala, Divyansh, et al.
Publicado: (2025)
LoGoFair: Post-Processing for Local and Global Fairness in Federated Learning
por: Zhang, Li, et al.
Publicado: (2025)
por: Zhang, Li, et al.
Publicado: (2025)
Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning
por: Wang, Yang, et al.
Publicado: (2025)
por: Wang, Yang, et al.
Publicado: (2025)
A Theoretical Framework for Graph-based Digital Twins for Supply Chain Management and Optimization
por: Wasi, Azmine Toushik, et al.
Publicado: (2025)
por: Wasi, Azmine Toushik, et al.
Publicado: (2025)
Ejemplares similares
-
Detecting Rug Pulls in Decentralized Exchanges: Machine Learning Evidence from the TON Blockchain
por: Yaremus, Dmitry, et al.
Publicado: (2025) -
The Origins of MEV: Systematic Attribution of Arbitrage Opportunity Creation at Scale
por: Seoev, Andrei, et al.
Publicado: (2026) -
SwarmRaft: Leveraging Consensus for Robust Drone Swarm Coordination in GNSS-Degraded Environments
por: Dev, Kapel, et al.
Publicado: (2025) -
Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction
por: Demidovich, Yury, et al.
Publicado: (2024) -
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
por: Li, Zhe, et al.
Publicado: (2024)