arXiv research

Study values and optimizes forestry leases under risk and uncertainty.

Study examines how disturbances affect financial returns in Austrian forests.

Study analyzes impacts of COVID-19 on French forestry sector, finds mixed results in supply chain.

Kriging is the predominant method used for spatial prediction, but relies on the assumption that predictions are linear combinations of the observations. Kriging often also relies on additional assumptions such as normality and stationarity. We propose a more flexible spatial prediction method based on the Nearest-Neig…

Semantic segmentation of land cover classes is fundamental for agricultural and economic development work, from sustainable forestry to urban planning, yet existing training datasets have significant limitations. To generate an open and comprehensive training library of high resolution Earth imagery and high quality la…

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

New models improve morpheme segmentation in low-resource languages.

A new algorithm for resource-aware multi-armed bandits minimizes regret.

Method selects significant spatial covariates in noisy data.

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

PePR scores assess DL model performance per resource unit, promoting smaller, more efficient models.

Forest management relies on the evaluation of silviculture practices. The increase in natural risk due to climate change makes it necessary to consider evaluation criteria that take natural risk into account. Risk integration in existing software requires advanced programming skills.We propose a user-friendly software …

Method learns software resource usage from snapshots.

Proposes a new framework for resource-limited recommendation.

Paper tackles pandemic resource allocation challenges.

PASHA optimizes model tuning for large datasets with limited resources.

Study resource allocation strategies in sequential decisions with unknown rewards.

This paper presents an assessment of global economic energy potentials for all major natural energy resources. This work is based on both an extensive literature review and calculations using natural resource assessment data. Economic potentials are presented in the form of cost-supply curves, in terms of energy flows …

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

Paper tackles non-monotonic resource utilization in sequential decision-making.

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

Deep learning enhances water resources management through data analysis.

Sequence-to-sequence models predict resource usage for co-scheduled jobs in data centers.

We consider multilingual bottleneck features (BNFs) for nearly zero-resource keyword spotting. This forms part of a United Nations effort using keyword spotting to support humanitarian relief programmes in parts of Africa where languages are severely under-resourced. We use 1920 isolated keywords (40 types, 34 minutes)…

Unified formula for arbitrary liquidity operations in weighted AMMs

This paper optimizes revenue and resource balance in network revenue management.

As deep neural network (NN) methods have matured, there has been increasing interest in deploying NN solutions to "edge computing" platforms such as mobile phones or embedded controllers. These platforms are often resource-constrained, especially in energy storage and power, but state-of-the-art NN architectures are de…

Caratheodory's axiom limits arbitrage in resource-limited systems.

Study introduces KorFinMTEB for Korean financial texts, revealing model limitations.

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

Review of efficient neural networks for TinyML on resource-constrained devices.

In urban environments, supply resources have to be constantly matched to the "right" locations (where customer demand is present) so as to improve quality of life. For instance, ambulances have to be matched to base stations regularly so as to reduce response time for emergency incidents in EMS (Emergency Management Sy…

Resource allocation improved using machine learning from terminal positions.

Method predicts hardware resource usage by control software with guaranteed linear convergence.

The study examines how quantum resources enhance the complexity of quantum circuits.

The study examines how alternative resource adequacy contract designs affect market participants' risk profiles and resource mix.

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…

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

The virtualization of compute and network resources enables an unseen flexibility for deploying network services. A wide spectrum of emerging technologies allows an ever-growing range of orchestration possibilities in cloud-based environments. But in this context it remains challenging to rhyme dynamic cloud configurat…

A new pricing controller handles resource constraints to infer target prices effectively.

The abstract discusses open data resources for studying and controlling the spread of COVID-19.

Algorithm tackles clustered contextual bandits with resource constraints.

A smart method predicts and optimizes decisions online with resource constraints.

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…

Driven by the tremendous technological advancement of personal devices and the prevalence of wireless mobile network accesses, the world has witnessed an explosion in crowdsourced live streaming. Ensuring a better viewers quality of experience (QoE) is the key to maximize the audiences number and increase streaming pro…

A model is presented in this work for simulating endogenously the evolution of the marginal costs of production of energy carriers from non-renewable resources, their consumption, depletion pathways and timescales. Such marginal costs can be used to simulate the long term average price formation of energy commodities. …

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…

Optimal online learning for joint pricing and resource allocation.