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Found 8 papers, 0 papers with code
Reinforcement Learning Paycheck Optimization for Multivariate Financial Goals
We study paycheck optimization, which examines how to allocate income in order to achieve several competing financial goals.
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
Motivated by applications in large-scale and multi-agent reinforcement learning, we study the non-asymptotic performance of stochastic approximation (SA) schemes with delayed updates under Markovian sampling.
A general theory for robust clustering via trimmed mean
In this paper, we introduce a hybrid clustering technique with a novel multivariate trimmed mean type centroid estimate to produce mislabeling guarantees under a weak initialization condition for general error distributions around the centroids.
ZeroSwap: Data-driven Optimal Market Making in DeFi
This ensures that the market maker balances losses to informed traders with profits from noise traders.
Adversarially robust clustering with optimality guarantees
In the absence of outliers, in fixed dimensions, our theoretical guarantees are similar to that of the Lloyd algorithm.
Real Time Analytics: Algorithms and Systems
Velocity is one of the 4 Vs commonly used to characterize Big Data.
Nonbacktracking Bounds on the Influence in Independent Cascade Models
This paper develops upper and lower bounds on the influence measure in a network, more precisely, the expected number of nodes that a seed set can influence in the independent cascade model.
The Application of Differential Privacy for Rank Aggregation: Privacy and Accuracy
The potential risk of privacy leakage prevents users from sharing their honest opinions on social platforms.
