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Found 14 papers, 2 papers with code
Mixed-Integer Projections for Automated Data Correction of EMRs Improve Predictions of Sepsis among Hospitalized Patients
In particular, by using high-dimensional mixed-integer programs that capture physiological and biological constraints on patient vitals and lab values, we can harness the power of mathematical "projections" for the EMR data to correct patient data.
TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Machine Learning
To this end, this paper introduces TACOS, an automated synthesizer that generates topology-aware collective algorithms for common distributed machine learning collectives across arbitrary input network topologies.
Artificial Intelligence/Operations Research Workshop 2 Report Out
This workshop Report Out focuses on the foundational elements of trustworthy AI and OR technology, and how to ensure all AI and OR systems implement these elements in their system designs.
Tree DNN: A Deep Container Network
TreeDNN helps in training the model with multiple datasets simultaneously, where each branch of the tree may need a different training dataset.
Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes
Motivated by this trade-off in runtime v/s convergence rates, we consider iterative projections of close-by points over widely-prevalent submodular base polytopes $B(f)$.
Algorithmic Challenges in Ensuring Fairness at the Time of Decision
The goal of this paper is to highlight the rich interface between temporal notions of fairness and online decision-making through a novel meta-objective of ensuring fairness at the time of decision.
Balanced Districting on Grid Graphs with Provable Compactness and Contiguity
Given a graph $G = (V, E)$ with vertex weights $w(v)$ and a desired number of parts $k$, the goal in graph partitioning problems is to partition the vertex set V into parts $V_1,\ldots, V_k$.
graph partitioning
Data Structures and Algorithms
Combinatorics
Optimization and Control
Multi-Threshold Attention U-Net (MTAU) based Model for Multimodal Brain Tumor Segmentation in MRI scans
Here, we have developed a multi-threshold model based on attention U-Net for identification of various regions of the tumor in magnetic resonance imaging (MRI).
Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization
We combine these insights into a novel Shadow-CG method that uses FW and shadow steps, while enjoying linear convergence, with a rate that depends on the number of breakpoints in its projection curve, rather than the pyramidal width.
Group-Fair Online Allocation in Continuous Time
Furthermore, as a consequence of certain ethical and economic concerns, the controller may impose deadlines on the completion of each task, and require fairness across different groups in the allocation of total time budget $B$.
Reducing the Feeder Effect in Public School Admissions: A Bias-aware Analysis for Targeted Interventions
These scores are known to be impacted by socioeconomic status of students and test preparation received in "feeder" middle schools, leading to a massive filtering effect in the education pipeline.
Robust Classification using Robust Feature Augmentation
Existing deep neural networks, say for image classification, have been shown to be vulnerable to adversarial images that can cause a DNN misclassification, without any perceptible change to an image.
Individual Fairness in Hindsight
In this paper, we extend the notion of IF to account for the time at which a decision is made, in settings where there exists a notion of conduciveness of decisions as perceived by the affected individuals.
Solving Combinatorial Games using Products, Projections and Lexicographically Optimal Bases
We give a general recipe to simulate the multiplicative weights update algorithm in time polynomial in their natural dimension.
