arXiv research

Deep RL tackles mmWave backhaul resource allocation challenges.

Optimal resource allocation in censored semi-bandits with unknown thresholds.

A new method for energy-efficient file delivery in small cell networks.

Multi-cell cooperative processing with limited backhaul traffic is studied for cellular uplinks. Aiming at reduced backhaul overhead, a sparsity-regularized multi-cell receive-filter design problem is formulated. Both unstructured distributed cooperation as well as clustered cooperation, in which base station groups ar…

Study resource allocation strategies in sequential decisions with unknown rewards.

Paper tackles pandemic resource allocation challenges.

This paper optimizes resource allocation for crowdsourced live streaming to improve viewer experience and reduce costs.

New loss function reduces outage probability in ML-assisted resource allocation.

Study optimizes resource allocation in noisy systems for better control.

Resource allocation improved using machine learning from terminal positions.

We study classification problems where features are corrupted by noise and where the magnitude of the noise in each feature is influenced by the resources allocated to its acquisition. This is the case, for example, when multiple sensors share a common resource (power, bandwidth, attention, etc.). We develop a method f…

Deep RL methods improve resource allocation in uncertain environments.

Unified formula for arbitrary liquidity operations in weighted AMMs

Lotteries improve resource allocation for players with complex preferences.

This paper proposes a decentralized reinforcement learning method for multi-agent resource allocation.

The densification of small-cell base stations in a 5G architecture is a promising approach to enhance the coverage area and facilitate the ever increasing capacity demand of end users. However, the bottleneck is an intelligent management of a backhaul/fronthaul network for these small-cell base stations. This involves …

Generative profiling improves real-time task timing for varied resource contexts.

The paper develops methods to optimize resource allocation in wireless systems using deep neural networks.

Optimizes resource allocation for virtualized network functions based on performance profiles.

Optimal online learning for joint pricing and resource allocation.

The paper tackles resource allocation for arms with unknown and random rewards, achieving optimal regret bounds.

Meta-DRL improves resource allocation in O-RAN networks.

The paper evaluates index-based allocation policies using data from randomized control trials.

Study on resource allocation with unknown thresholds in semi-bandit problems.

ATA optimizes task allocation in distributed machine learning.

We study a sequential resource allocation problem between a fixed number of arms. On each iteration the algorithm distributes a resource among the arms in order to maximize the expected success rate. Allocating more of the resource to a given arm increases the probability that it succeeds, yet with a cut-off. We follow…

An adaptive algorithm optimizes resource allocation with diminishing returns.

RL optimizes resource allocation in MG by balancing experience and exploration.

Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the unde…

Improved resource allocation method reduces procurement costs.

Federated Learning over wireless networks tackles resource allocation challenges.

PASHA optimizes model tuning for large datasets with limited resources.

Study develops a smart contract framework for efficient and fair resource allocation.

New estimator improves policy evaluation in resource allocation RCTs.

Some agent-based models for growth and allocation of resources are described. The first class considered consists of conservative models, where the number of agents and the size of resources are constant during time evolution. The second class is made up of multiplicative noise models and some of their extensions to co…

Develops deep learning for optimizing 5G radio resource allocation.

Framework for online resource allocation using social welfare functions.

Paper proposes OPF policy for fair resource allocation with sublinear regret.

Designs for allocating resources to prioritize needy applicants while estimating treatment effects.

New algorithm tackles resource allocation in multi-armed bandits to balance speed and throughput.

Algorithm allocates perishable resources online to minimize envy and inefficiency.

This work tackles resource allocation in asynchronous and stochastic systems.

Study efficient resource allocation for detecting extreme values.

This paper optimizes cybersecurity resource allocation in networks with heterogeneous attacker and defender valuations.

An active learning approach reduces AoI violation in vehicular networks.

Uber optimizes marketplace levers using machine learning to improve resource allocation efficiency.

Adaptive RL optimizes testing resource allocation for dynamic software environments.

Paper addresses FL over wireless networks, optimizing learning and resource allocation.