Decentralized detection avoids sharing data, controls false discoveries.
problem Global false discovery rate control in decentralized novelty detection.
method Quantized surrogate models for low-precision sharing, preserving exchangeability.
result Quantized composite scores maintain competitive statistical power with reduced communication.
New algorithm for multi-player bandits in decentralized, asynchronous systems.
problem Challenges in decentralized, asynchronous multi-player bandits, including coordination and player detection.
method Adaptive exploration-exploitation algorithm that reduces collisions and detects player presence.
result Achieves regret of O ( T log T + log T / Δ 2 ) \mathcal{O}(\sqrt{T \log T} + {\log T}/{Δ^2}) O ( T log T + log T / Δ 2 ) . Paper introduces ITD for detecting distributional changes in decentralized learning environments.
problem Detecting distributional changes in decentralized learning environments with data privacy and heterogeneity concerns.
method Introduces Integrated Transportation Distance (ITD) for two-sample testing in federated learning.
result ITD effectively aggregates information across distributed clients, detecting subtle distributional shifts.
The problem of secure friend discovery on a social network has long been proposed and studied. The requirement is that a pair of nodes can make befriending decisions with minimum information exposed to the other party. In this paper, we propose to use community detection to tackle the problem of secure friend discovery…
ETHGamDet detects crypto gambling contracts and addresses.
problem Identifying crypto gambling contracts and addresses.
method Multi-modal retrieval methods, LightGBM model with memory components.
result ETHGamDet achieves high F1-scores in address and contract classification.
New algorithm finds more arbitrage opportunities in DEXs.
problem Detecting arbitrage loops and non-loops in decentralized exchanges.
method Combining line graph and modified Moore-Bellman-Ford algorithm.
result Found more arbitrage loops and non-loops compared to existing methods.
The paper provides Gaussian approximations for decentralized Federated Learning.
problem Lack of asymptotic statistical guarantees for local SGD in Federated Learning.
method Two generalized Gaussian approximation results for local SGD trajectories.
result Valid multiplier bootstrap procedures and Gaussian bootstrap-based tests for detecting adversarial attacks.
Enhances Ponzi scheme detection on Ethereum using time-aware metapaths.
problem Lack of temporal information in heterogeneous transaction graphs.
method Time-aware Metapath Feature Augmentation (TMFAug) module.
result Significant performance improvements in Ponzi scheme detection.
New algorithms detect anomalies in processes with minimal delay.
problem Sequentially selecting and observing processes to identify anomalies.
method Developed centralized and decentralized anomaly detection algorithms using reinforcement learning.
result Minimizes delay in decision making while identifying anomalies accurately.
The paper proposes a machine learning framework for detecting DeFi fraud across multiple blockchain chains.
problem Early detection of financial crimes in decentralized finance (DeFi) ecosystems.
method Extracting features from different blockchain chains, employing XGBoost and Neural Network for fraud detection.
result Introduction of novel DeFi-related features significantly improves fraud detection accuracy.
Despite the overwhelming success of the existing Social Networking Services (SNS), their centralized ownership and control have led to serious concerns in user privacy, censorship vulnerability and operational robustness of these services. To overcome these limitations, Distributed Social Networks (DSN) have recently b…
Three methods detect informed trading on prediction markets, each focusing on different aspects.
problem Detecting informed trading in decentralized prediction markets.
method Composite screen, event-level sign-randomization test, and Information Leakage Score (ILS) framework.
result Different methods detect informed trading on prediction markets, each focusing on different aspects.
This study compares decentralized banks and finds some lack decentralization.
problem Decentralized banks do not fully decentralize transactions as expected.
method Network analysis of transaction data from four banks using core-periphery features.
result MakerDao and Compound are more decentralized than Aave and Liquity.
Systematizes blockchain decentralization taxonomy and metrics.
problem Lack of a unified definition for blockchain decentralization.
method Formulated a taxonomy of five facets and developed metrics.
result Provided comprehensive insights into blockchain decentralization.
Paper uses GNNs to automatically detect botnets from network data.
problem Detecting botnets from network data using traditional methods is challenging.
method Synthesized botnet connections, tailored graph neural networks (GNNs), and deep learning.
result GNNs outperform traditional methods in botnet detection.
JIT liquidity providers can sometimes reduce overall market liquidity by crowding out passive LPs.
problem JIT liquidity providers can reduce overall market liquidity by crowding out passive LPs.
method Game-theoretic model with asymmetrically informed agents to analyze JIT liquidity provision in blockchain-based decentralized exchanges.
result JIT LPs only provide liquidity to uninformed orders and crowd out passive LPs when order volume is not sufficiently elastic to pool depth, potentially reducing overall market liquidity.
Study finds Aave token network has core-periphery structure, with high decentralization predicting better returns.
problem Understanding the actual decentralization in DeFi token transactions on the Ethereum blockchain.
method Applied social network analysis to measure decentralization in Aave token transactions.
result A more decentralized Aave token network predicts higher returns and lower volatility.
MakerDAO's governance is centralized despite its decentralized claim.
problem Decentralization illusion in Decentralized Finance (DeFi) governance.
method Empirical analysis using financial, transaction, network, and sentiment indicators.
result Centralized governance impacts Maker protocol and voting power distribution.
The paper analyzes distributed Bayesian inference and its Frequentist guarantees.
problem Analyzing large decentralized datasets with distributed Bayesian inference.
method Establishes Frequentist properties for distributed (non-)Bayesian inference.
result Distributed Bayesian inference retains parametric efficiency and enhances robustness.
Decentralized finance uses blockchain for $70B in assets, differing from traditional finance.
problem Ensuring compliance and security in decentralized finance.
method Systematic analysis of legal, economic, security, and privacy aspects.
result Decentralized finance offers unique economic effects and security features.
This paper analyzes voter coalitions in MakerDAO's decentralized governance.
problem Understanding the governance structure and influence of voter coalitions in DAOs.
method Applied clustering algorithm to voting history of MakerDAO to identify voter coalitions.
result The emergence of a dominant voter coalition signals governance centralization in DAOs.
Study on decentralization in DAOs and its effect on financial efficiency in DeFi.
problem Understanding the impact of decentralization on financial efficiency in blockchain-based governance.
method Analysis using Gini coefficient as an inequality indicator, comparing ROI of token owners.
result Real decentralization affects financial efficiency positively in DeFi.
Graph learning categorizes DeFi services into similar functionalities.
problem Identifying similar financial services in decentralized finance protocols.
method Graph representation learning (GRL) to categorize smart contract blocks into clusters.
result Purity of clustering reaches .888 in the best-case scenario.
The paper examines Bitcoin's nature using fractal geometry and finds it highly persistent, affecting predictability and decentralization.
problem Understanding the nature and predictability of Bitcoin prices.
method Statistical analysis of Bitcoin returns using fractal geometry.
result Bitcoin exhibits high persistence in prices, reducing efficiency but increasing predictability.
The paper analyzes stability and generalization of decentralized SGD.
problem Stability and generalization of decentralized stochastic gradient descent.
method Novel formulation of decentralized stochastic gradient descent combined with non/convex optimization theory.
result First stability and generalization guarantees for decentralized stochastic gradient descent.
New CUSUM method detects changes in Hawkes networks efficiently.
problem Detecting abrupt changes in Hawkes networks.
method Efficient online recursive implementation of CUSUM statistic.
result Proposed CUSUM method outperforms existing methods.
NFTs raise concerns like scams, racism, and sexism; centralization vs decentralization debate.
problem Concerns and value judgments of stakeholders in NFT market.
method Mixed quantitative and qualitative methods: social media analysis and interviews.
result Identified financial scams, counterfeit NFTs, hacking, and unethical NFTs as major issues.
A decentralized approach for multi-source domain adaptation.
problem Transfer knowledge from multiple related domains to an unlabeled target domain.
method Federated Dataset Dictionary Learning (FedDaDiL) framework, eliminating central server, using Wasserstein barycenters.
result Our decentralized approach effectively adapts source domains to an unlabeled target domain.
Decentralized Gaussian processes for multi-agent learning.
problem Training and prediction in multi-agent systems.
method Decentralized ADMM for GP hyper-parameter training and iterative consensus for prediction.
result Subset of agents can perform predictions using covariance-based nearest neighbor selection.
Paper tightens lower bounds on decentralized training complexity.
problem Understanding and optimizing iteration complexity in decentralized training.
method Proved a tight lower bound on iteration complexity and proposed DeTAG algorithm.
result DeTAG achieves the theoretical lower bound with only a logarithmic gap.
This study measures decentralization in blockchain finance governance.
problem Defining and measuring decentralization in blockchain finance applications.
method Aggregating and analyzing empirical data of four finance applications to calculate coefficients for governance token distribution.
result Gauges for objective evaluation of token governance capabilities and limitations.
Paper proposes decentralized annuities for better retirement security.
problem Current pension systems' limitations and fairness issues.
method Theoretical models and fairness concepts analysis.
result Decentralized annuities offer enhanced flexibility and social welfare.
The paper analyzes risks and revenue dynamics of a liquid restaking protocol in decentralized finance.
problem Interconnected risks and revenue dynamics of a liquid restaking protocol in decentralized finance.
method Empirical analysis using OLS regression, Granger-causality, and random forest feature importance tests.
result Revenue is primarily driven by value locked in the ecosystem, yield of liquid restaking token, and multi-blockchain expansion.
Communication is a key bottleneck in distributed training. Recently, an \emph{error-compensated} compression technology was particularly designed for the \emph{centralized} learning and receives huge successes, by showing significant advantages over state-of-the-art compression based methods in saving the communication…
Enhances parallelism in decentralized learning for larger networks.
problem Scalability limitations in decentralized learning with increasing number of machines.
method Proposes Decentralized Anytime SGD, a novel algorithm that extends parallelism threshold.
result Establishes a theoretical upper bound on parallelism surpassing current state-of-the-art.
Novel periodic momentum SGD method for decentralized training with linear speedup.
problem Lack of effective momentum schema in decentralized training methods.
method Proposes a novel periodic decentralized momentum SGD method.
result Achieves linear speedup in decentralized training.
Single global merging boosts decentralized learning performance.
problem Limited communication in decentralized learning hinders performance.
method Scheduled communication, focusing on final step with global merging.
result Single global merging improves global test performance.
Bayesian algorithms minimize cumulative regret in decentralized multi-agent bandits.
problem Minimizing cumulative regret in a decentralized multi-agent multi-armed bandit problem.
method Proposed decentralized Bayesian multi-armed bandit framework, including Thompson Sampling and Bayes-UCB algorithms.
result Regret scales logarithmically with constants matching those of an optimal centralized agent.
Unified framework for decentralized bilevel optimization with various heterogeneity-correction strategies.
problem Decentralized bilevel optimization with neighborhood communications and data heterogeneity.
method SPARKLE: Single-loop Primal-dual Algorithm for decentralized bilevel optimization, incorporating various heterogeneity-correction techniques.
result Unified convergence analysis for SPARKLE with state-of-the-art convergence rates compared to existing algorithms.
Flexible decentralized MARL framework for cooperative multi-agent learning.
problem Complexity and impracticality of centralized MARL in complicated applications.
method Flexible fully-decentralized actor-critic MARL framework using primal-dual hybrid gradient descent.
result Competitive performance in large-scale cooperative multi-agent environments.
New algorithms for Bayesian inference in decentralized learning.
problem Bayesian inference in decentralized learning settings.
method Decentralized SGLD and Decentralized SGHMC.
result Convergence of iterates to target distribution in 2-Wasserstein distance.
This research compiles knowledge on decentralized exchanges with AMM protocols.
problem Improving and developing AMM-based decentralized exchanges.
method Established a general AMM framework, compared mechanics, discussed security and privacy.
result Illustrated conservation and slippage functions of AMM protocols.
Quantum self-attention boosts automated market maker performance in crypto trading.
problem Improving automated market maker rebalancing in crypto trading.
method Quantum Adaptive Self-Attention (QASA) using variational quantum circuits and softmax attention.
result QASA-Sequence variant achieves best single-model risk-adjusted performance in crypto trading.
This paper improves privacy accounting in decentralized FL using f-Differential Privacy.
problem Challenges in accurately quantifying privacy budget in decentralized FL.
method Develops two new f-DP-based accounting methods for decentralized FL.
result Yields tighter (ε,δ) bounds and improved utility compared to existing methods.
DE-PSGLD samples from constrained distributions in a decentralized manner.
problem Sampling from log-concave distributions with constraints.
method Decentralized Proximal Stochastic Gradient Langevin Dynamics with proximal regularization.
result DE-PSGLD converges to a regularized Gibbs distribution and maintains posterior concentration.
A framework for decentralized optimization using first-order methods.
problem Optimization of finite sums over networked nodes.
method Decentralized first-order gradient and stochastic methods.
result General framework for undirected and directed networks.
Graph neural networks learn decentralized controllers from data.
problem Finding optimal decentralized controllers for autonomous agents is challenging.
method Adapting graph neural networks to handle delayed communications and ensure scalability and transferability.
result Graph neural networks can learn decentralized controllers from data, addressing the scalability and practical implementation issues of centralized controllers.
This paper creates a comprehensive BTC transaction network dataset spanning 15 years.
problem Lack of a full-history BTC graph and network property dataset.
method Thorough analysis of BTC transaction network, creating a dataset and investigating decentralization.
result First systematic investigation of BTC's asset decentralization and design of decentralization degrees.