arXiv research

Paper introduces score embedding for Twitter sentiment analysis of health care issues.

We model the quantities appearing in Internal Revenue Service (IRS) tax guidance for calculating the health insurance premium tax credit created by the Patient Protection and Affordable Care Act, also called Obamacare. We ask the question of whether there is a procedure, computable by hand, which can calculate the appr…

Model predicts wound and episode-level readmission risk and time to re-admit.

HAL learns hierarchical affordances to prune impossible subtasks, improving reinforcement learning efficiency.

Proposes a fix for IRS calculation of Obamacare tax credits.

The paper introduces affordances for reinforcement learning, improving planning and learning efficiency.

Model learns tool affordances from vision, enabling tool selection.

Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be per…

Intensive care clinicians are presented with large quantities of patient information and measurements from a multitude of monitoring systems. The limited ability of humans to process such complex information hinders physicians to readily recognize and act on early signs of patient deterioration. We used machine learnin…

One of the open challenges in designing robots that operate successfully in the unpredictable human environment is how to make them able to predict what actions they can perform on objects, and what their effects will be, i.e., the ability to perceive object affordances. Since modeling all the possible world interactio…

We consider the Neumann Laplacian acting on square-integrable functions on a triangle in the hyperbolic plane that has one cusp. We show that the generic such triangle has no eigenvalues embedded in its continuous spectrum. To prove this result we study the behavior of the real-analytic eigenvalue branches of a degener…

Develops models for temporally abstract reasoning and attention.

Novel RL method handles urban driving tasks including traffic lights.

Recent introduction of wearable single-lead ECG devices of diverse configurations has caught the intrigue of the medical community. While these devices provide a highly affordable support tool for the caregivers for continuous monitoring and to detect acute conditions, such as arrhythmia, their utility for cardiac diag…

Collage-CNN reduces cloud inference latency by 1.47X with 9X reduced latency variation.

New PCGML approach generates novel game content across multiple platformer domains.

Propagates adversarial robustness in federated learning.

New AI model optimizes personalized care for elderly residents.

Gradient Descent with small random initialization solves rank-1 matrix completion efficiently.

Let $M$ be a closed, connected, orientable topological four-manifold with $H_1(M)$ nontrivial and free abelian, $b_2(M)\ne 0, 2$, and $χ(M)\ne 0$. We show that if $G$ is a finite group of 2-rank $\le 1$ which admits a homologically trivial, locally linear, effective action on $M$, then $G$ must be cyclic. With addition…

Deep RL controls anesthesia more accurately than traditional methods.

The study uses machine learning to analyze office floor plans and predict function based on geometry.

The paper presents a method to score patient engagement in care programs and predicts their response.

Model predicts COVID-19 growth in Senegal, highlighting health care capacity importance.

The study shows that certain manifolds with positive curvature cannot contain specific geometric structures.

We address the problem of bootstrapping language acquisition for an artificial system similarly to what is observed in experiments with human infants. Our method works by associating meanings to words in manipulation tasks, as a robot interacts with objects and listens to verbal descriptions of the interactions. The mo…

Improving the quality of end-of-life care for hospitalized patients is a priority for healthcare organizations. Studies have shown that physicians tend to over-estimate prognoses, which in combination with treatment inertia results in a mismatch between patients wishes and actual care at the end of life. We describe a …

CARE improves LLM aggregation by accounting for shared confounders.

We define a finite-dimensional cubic quotient of the group algebra of the braid group, endowed with a (essentially unique) Markov trace which affords the Links-Grould invariant of knots and links. We investigate several of its properties, and state several conjectures about its structure.

Public benchmark for machine learning models in critical care.

Paper develops new algorithms for unsupervised multi-class domain adaptation.

Study on privacy-preserving health care models that sacrifice accuracy for data protection.

Inpatient care is a large share of total health care spending, making analysis of inpatient utilization patterns an important part of understanding what drives health care spending growth. Common features of inpatient utilization measures include zero inflation, over-dispersion, and skewness, all of which complicate st…

Mathematical models help keep vaccine prices low.

System predicts HIV patients at risk of dropping out of care.

This work trains a model to predict human driving directions from road scenes.

Estimates causal effect of managed care plans on NYC Medicaid spending.

Accurate classification of self-care problems in children who suffer from physical and motor affliction is an important problem in the healthcare industry. This is a difficult and a time consumming process and it needs the expertise of occupational therapists. In recent years, healthcare professionals have opened up to…

LHIEM model predicts health, income, and employment over years.

We present a survey of the calibrated geometries arising in the study of the local singularity structure of supersymmetric fivebranes in M-theory. We pay particular attention to the geometries of 4-planes in eight dimensions, for which we present some new results as well as many details of the computations. We also ana…

Data analytics using machine learning (ML) has become ubiquitous in science, business intelligence, journalism and many other domains. While a lot of work focuses on reducing the training cost, inference runtime and storage cost of ML models, little work studies how to reduce the cost of data acquisition, which potenti…

We consider composite loss functions for multiclass prediction comprising a proper (i.e., Fisher-consistent) loss over probability distributions and an inverse link function. We establish conditions for their (strong) convexity and explore the implications. We also show how the separation of concerns afforded by using …

AdvImmune improves certifiable robustness of GNNs against adversarial attacks.

Clinical decision making is challenging because of pathological complexity, as well as large amounts of heterogeneous data generated as part of routine clinical care. In recent years, machine learning tools have been developed to aid this process. Intensive care unit (ICU) admissions represent the most data dense and t…

Characterizes Fredholm conditions for group-invariant pseudodifferential operators.

This work aims to create a large-scale model for critical care time series data.

Graph-based methods pervade the inference toolkits of numerous disciplines including sociology, biology, neuroscience, physics, chemistry, and engineering. A challenging problem encountered in this context pertains to determining the attributes of a set of vertices given those of another subset at possibly different ti…

A new model framework called Realized Conditional Autoregressive Expectile (Realized-CARE) is proposed, through incorporating a measurement equation into the conventional CARE model, in a manner analogous to the Realized-GARCH model. Competing realized measures (e.g. Realized Variance and Realized Range) are employed a…