arXiv research

New neural network reduces CT radiation, works for any ROI size.

Deep learning improves ROI reconstruction in low-dose CT.

Simulation framework assesses ROI of chronic disease adherence and policy timing.

New analysis shows ROI's predictive power for stock returns weakens significantly.

New algorithm for quickly deciding on tech innovations to maximize ROI.

Model predicts sponsorship ROI using renewal probability.

A novel approach for 3D lung nodule segmentation using adaptive ROI and multi-view residual learning.

BALLET filters a high-confidence region of interest for Bayesian optimization.

ROI-driven data analytics guides investment in empirical data analysis.

BrainCast predicts whole-brain fMRI time series from short scans.

A two-stage CNN approach for brain tumor segmentation.

Deep learning method for brain CT scan anomaly labeling using nearest neighbors.

Project forecasts crop prices to help Indian farmers choose optimal crops for better ROI.

PR-GNN identifies salient brain regions for ASD biomarkers.

Study optimizes health incentives to balance efficiency and fairness.

Roy's `Safety First' criterion for selecting one risky asset from many is adapted to the case of non-normal returns, via Cornish Fisher expansion. The resulting investment objective is consistent with first order stochastic dominance, and is equal to the Sharpe ratio for the case of normal returns. An investor selectin…

ROIreg refines CNN's classification ability by focusing on pixel blocks.

Reduced computational complexity for indoor positioning.

We study the performance of various agent strategies in an artificial investment scenario. Agents are equipped with a budget, $x(t)$, and at each time step invest a particular fraction, $q(t)$, of their budget. The return on investment (RoI), $r(t)$, is characterized by a periodic function with different types and leve…

Model predicts stock prices using GAN and RoI Pooling.

Researchers in functional neuroimaging mostly use activation coordinates to formulate their hypotheses. Instead, we propose to use the full statistical images to define regions of interest (ROIs). This paper presents two machine learning approaches, transfer learning and selection transfer, that are compared upon their…

Efficiently explores concurrent RL agents for practical scale problems.

Proposes a methodology to improve data science ROI by addressing key business questions.

Multivariate Pattern (MVP) classification holds enormous potential for decoding visual stimuli in the human brain by employing task-based fMRI data sets. There is a wide range of challenges in the MVP techniques, i.e. decreasing noise and sparsity, defining effective regions of interest (ROIs), visualizing results, and…

Develops a framework to estimate NBA player salary ROI.

Dynamic promotion optimization for e-commerce platforms within financial constraints.

Generative Adversarial Model improves RV segmentation accuracy in MRI.

The paper extends Thompson Sampling to infinite action spaces using information theory.

G3M impermanent losses are a key issue in decentralized finance, affecting diversification benefits.

Automatically classifying the tissues types of Region of Interest (ROI) in medical imaging has been an important application in Computer-Aided Diagnosis (CAD), such as classification of breast parenchymal tissue in the mammogram, classify lung disease patterns in High-Resolution Computed Tomography (HRCT) etc. Recently…

The paper tightens the regret rate for linear bandit problems.

The paper uses distance correlation for brain connectivity and a novel multi-task learning model for age prediction.

Study analyzes cost-benefit of CBM for unmanned systems.

Paper optimizes trading profits by predicting price direction using ensemble models.

We analyze the possibility of reduction of systemic risk in financial markets through Pigouvian taxation of financial institutions which is used to support the rescue fund. We introduce the concept of the cascade risk with a clear operational definition as a subclass and a network related measure of the systemic risk. …

The paper analyzes ESS metrics and their connections to entropy families.

The author proposes a finance trading strategy named Entropy Oriented Trading and apply thermodynamics on the strategy. The state variables are chosen so that the strategy satisfies the second law of thermodynamics. Using the law, the author proves that the rate of investment (ROI) of the strategy is equal to or more t…

Study on decentralization in DAOs and its effect on financial efficiency in DeFi.

Inter-subject registration of cortical areas is necessary in functional imaging (fMRI) studies for making inferences about equivalent brain function across a population. However, many high-level visual brain areas are defined as peaks of functional contrasts whose cortical position is highly variable. As such, most ali…

A mixture of experts model predicts brain activation from word stimuli.

Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on analysis of previous work, sometimes formalized in a so-called meta-analysis. In brain imaging, this approach underlies th…

New algorithm finds optimal policy with polynomial trajectories in deterministic systems.

Develops a new method to analyze brain networks for cognitive traits.

We introduce the Mondrian kernel, a fast random feature approximation to the Laplace kernel. It is suitable for both batch and online learning, and admits a fast kernel-width-selection procedure as the random features can be re-used efficiently for all kernel widths. The features are constructed by sampling trees via a…

Mirror descent linked to information ratio via Bayesian regret bounds.

We construct a new map from a convex function to a distribution on its domain, with the property that this distribution is a multi-scale exploration of the function. We use this map to solve a decade-old open problem in adversarial bandit convex optimization by showing that the minimax regret for this problem is $\tild…

Stochastic model prices weather derivatives for Indian states, highlighting temperature volatility impacts.

A new method clusters subjects based on brain networks without vectorizing fMRI data.