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.
Running Stochastic Gradient Descent (SGD) in a decentralized fashion has shown promising results. In this paper we propose Moniqua, a technique that allows decentralized SGD to use quantized communication. We prove in theory that Moniqua communicates a provably bounded number of bits per iteration, while converging at …
FedFaiREE addresses fairness in decentralized learning with small samples.
problem Ensuring fairness in decentralized federated learning with limited data.
method FedFaiREE is a post-processing algorithm for distribution-free fair learning in decentralized settings with small samples.
result FedFaiREE provides theoretical guarantees for both fairness and accuracy in decentralized environments.
Research examines how strategic latency manipulation impacts Ethereum's network efficiency and decentralization.
problem Impact of artificial latency on Ethereum's network efficiency and decentralization.
method Comprehensive analysis of MEV-Boost auction system and empirical validation with a pilot.
result Increased profitability for node operators and significant systemic challenges like heightened network inefficiencies and centralization risks.
Decentralized stochastic gradient method emerges as a promising solution for solving large-scale machine learning problems. This paper studies the decentralized Markov chain gradient descent (DMGD) algorithm - a variant of the decentralized stochastic gradient methods where the random samples are taken along the trajec…
DECS tool assesses swap rates of DEXes and Fusion outperforms competitors.
problem Lack of unbiased swap rate comparisons in decentralized finance.
method Swap transaction monitoring and simulation techniques.
result 1inch Classic and Fusion consistently outperform competitors in swap rates.
OpenAlpha validates decentralized capital strategies using game theory and market aggregation.
problem Decentralized capital management's lack of trust-minimised, adaptive deployment.
method Game-theoretic validation, adversarial auditing, market-based belief aggregation.
result Confidence scores from validation phases inform capital allocation rules.
Recently, the decentralized optimization problem is attracting growing attention. Most existing methods are deterministic with high per-iteration cost and have a convergence rate quadratically depending on the problem condition number. Besides, the dense communication is necessary to ensure the convergence even if the …
Unified framework for Byzantine robust gossip algorithms with guaranteed performance.
problem Vulnerability of decentralized machine learning to misbehaving devices.
method Introduces F-RG framework and CS+ robust aggregation rule for Byzantine resilience.
result CS+-RG has near-optimal breakdown tolerance and outperforms 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.
Paper tackles efficient SVM classification over decentralized networks.
problem Efficiently classifying high-dimensional data over decentralized networks.
method Convolution-based smoothing technique for nonsmooth hinge loss function, combined with an efficient ADMM algorithm.
result Provable linear convergence of the ADMM algorithm and near-optimal statistical convergence of the sparse estimator.
Decentralized optimization on dynamic manifolds with improved regret bound.
problem Optimizing on nonstationary Riemannian manifolds in decentralized systems.
method Decentralized projected Riemannian gradient descent with weighted Frechet mean consensus.
result Achieved dynamic regret bound of O ( T ( 1 + P T ) / ( 1 − σ 2 ( W ) ) ) {\cal O}(\sqrt{T(1+P_T)}/\sqrt{(1-σ_2(W))}) O ( T ( 1 + P T ) / ( 1 − σ 2 ( W )) ) . Centralized exchanges influence staking behavior and decentralization in Proof of Stake blockchain ecosystems.
problem How do centralized exchanges affect staking behavior and decentralization in Proof of Stake blockchain ecosystems?
method Formulate a continuous-time mean field model of miners as validators and traders in a centralized market.
result Centralized trading activities enhance staking participation and promote decentralization through market incentives.
LEAD algorithm speeds up decentralized optimization with compression.
problem Slow convergence and stability issues in decentralized optimization with compression.
method Proposes the first linearly convergent decentralized algorithm with compression.
result First consensus error bound for coupled dynamics of primal and dual updates.
Decentralized mechanism for collective predictions without sharing data or models.
problem Making predictions jointly among multiple parties without sharing data or models.
method Inspired by social science consensus-making, a decentralized mechanism for test-time collective predictions.
result Our mechanism converges to inverse meansquared-error weighting in the large-sample limit and achieves significant gains over classical model averaging.
Experts predict significant adoption of decentralized finance by 2034, with traditional finance adapting.
problem Adoption and integration of decentralized finance (DeFi) in financial services.
method Survey analysis using New Institutional Economics and Dynamic Capabilities Theory.
result Experts expect adoption of DeFi to rise from negligible to 43% by 2034, with traditional finance likely to embrace it.
Paper introduces MoTEF for faster decentralized optimization with compressed communication.
problem Efficiency bottleneck in decentralized machine learning applications.
method Integrates communication compression with Momentum Tracking and Error Feedback.
result Significantly outperforms existing methods under arbitrary data heterogeneity.
Most distributed machine learning systems nowadays, including TensorFlow and CNTK, are built in a centralized fashion. One bottleneck of centralized algorithms lies on high communication cost on the central node. Motivated by this, we ask, can decentralized algorithms be faster than its centralized counterpart? Althoug…
New gossip algorithms improve robustness of rank-based statistics in decentralized systems.
problem Ensuring robustness in decentralized AI and edge intelligence systems, especially in the presence of corrupted or adversarial data.
method Developed asynchronous gossip algorithms for computing rank-based statistics.
result First convergence rate bound for asynchronous gossip-based rank estimation.
Paper introduces Decentralized Non-stationary Competing Bandits ( exttt{DNCB}) for dynamic matching markets.
problem Understanding dynamic two-sided matching markets with competing agents.
method Proposes a decentralized asynchronous learning algorithm ( exttt{DNCB}) for non-stationary environments.
result Obtains sub-linear (logarithmic) regret of exttt{DNCB} in dynamic settings.
Decentralized Online Learning (online learning in decentralized networks) attracts more and more attention, since it is believed that Decentralized Online Learning can help the data providers cooperatively better solve their online problems without sharing their private data to a third party or other providers. Typical…
DIGing-SGLD improves SGLD for scalable Bayesian learning in dynamic networks.
problem Scalable Bayesian learning in multi-agent systems with time-varying networks.
method Integrates Langevin sampling with gradient-tracking for decentralized learning over time-varying networks.
result Achieves geometric convergence to the target distribution with finite-time guarantees.
Optimizing distributed learning systems is an art of balancing between computation and communication. There have been two lines of research that try to deal with slower networks: {\em communication compression} for low bandwidth networks, and {\em decentralization} for high latency networks. In this paper, We explore a…
We propose an efficient protocol for decentralized training of deep neural networks from distributed data sources. The proposed protocol allows to handle different phases of model training equally well and to quickly adapt to concept drifts. This leads to a reduction of communication by an order of magnitude compared t…
Modeling gas fee competition in decentralized exchanges to optimize arbitrage profits.
problem Gas fees and transaction ordering in decentralized exchanges create arbitrage opportunities.
method Developed a first equilibrium model of gas fee competition between two arbitrageurs under three transaction reversion settings.
result Mixed equilibria exist, and their characteristics depend on inventory risk and transaction settings.
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 ) . This paper studies the problem of error-runtime trade-off, typically encountered in decentralized training based on stochastic gradient descent (SGD) using a given network. While a denser (sparser) network topology results in faster (slower) error convergence in terms of iterations, it incurs more (less) communication …
Partner-aware algorithms improve AI collaboration in multi-agent settings.
problem Improving AI cooperation in teams with shared rewards.
method Proposed Partner-Aware strategy extending Upper Confidence Bound for decentralized MAB.
result Achieves logarithmic regret in collaborative decision-making.
This study interprets AMM fees as implied volatility, validating their relevance in digital asset markets.
problem Understanding the volatility of fees in decentralized exchange systems.
method Reinterpreting AMM fees as implied volatility and applying fixed-for-floating swaps to quote and validate these volatilities.
result The implied volatilities of digital assets can be accurately quoted using AMM fees, validating the approach.
We consider the problem of \emph{fully decentralized} multi-agent reinforcement learning (MARL), where the agents are located at the nodes of a time-varying communication network. Specifically, we assume that the reward functions of the agents might correspond to different tasks, and are only known to the corresponding…
LG algorithm finds profitable trading paths in decentralized exchanges.
problem Identifying optimal trading paths in decentralized exchanges.
method Line-graph-based algorithm (LG) for efficient route discovery.
result LG consistently identifies more profitable paths than DFS with comparable costs.
SONATA algorithm converges to solutions of nonconvex smooth functions with KL property.
problem Decentralized optimization over networks with nonconvex smooth functions and convex constraints.
method Decentralized gradient-tracking algorithm SONATA under the KL property.
result SONATA converges to stationary solutions at R-linear rate for θ ∈ ( 0 , 1 / 2 ] θ\in (0,1/2] θ ∈ ( 0 , 1/2 ] , sublinear rate for θ ∈ ( 1 / 2 , 1 ) θ\in (1/2,1) θ ∈ ( 1/2 , 1 ) , and R-linear rate for θ = 0 θ=0 θ = 0 . 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.
New approach estimates treatment effects from decentralized data.
problem Estimating treatment effects from multiple studies with limited data.
method Three classes of ATE estimators derived from Plug-in G-Formula.
result Asymptotic variance of estimators for linear models derived.
New algorithm for decentralized online convex optimization with unknown delays.
problem Decentralized online convex optimization with unknown, time-varying feedback delays.
method Proposes a novel algorithm that incorporates adaptive learning rates and gossip-based delay estimation.
result Achieves improved regret bounds of O(N √d tot + N √T (1-σ^2)^(1/4)) and O(N δmax ln T α) for different settings.
The paper tackles dynamic collateral control for spot-perpetual basis trading in decentralized finance.
problem Dynamic control of collateral in spot-perpetual basis trading in decentralized finance.
method Solves a static control problem and derives an asymmetric dynamic extension, validated with live execution.
result The dynamic control approach provides a more robust operating benchmark and shows significant rebalancing effects.
This work introduces uncertainty principles to mitigate Maximal Extractable Value in blockchain systems.
problem Maximal Extractable Value (MEV) in decentralized systems due to transaction submission privacy and monopolist power.
method Unified approaches via uncertainty principles, akin to harmonic analysis and physics, to quantify trade-offs between transaction flexibility and user economic payoff.
result Demonstrates a quantitative trade-off between transaction flexibility and user economic payoff, analogous to the Nyquist-Shannon sampling theorem.
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.
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.
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.
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.