Coordinate Descent with Bandit Sampling

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Overview This dataset provides high-resolution, georeferenced vehicle trajectories collected via drone footage at three roundabouts located in the municipalities of Frick and Laufenburg, Canton of Aargau, Switzerland. The data were collected as part of a ...

Generative language models (LMs) have become omnipresent across data science. For a wide variety of tasks, inputs can be phrased as natural language prompts for an LM, from whose output the solution can then be extracted. LM performance has consistently be ...

The scale and pervasiveness of the Internet make it a pillar of planetary communication, industry and economy, as well as a fundamental medium for public discourse and democratic engagement. In stark contrast with the Internet's decentralized infrastructur ...

In this work we consider an online learning problem, called Online k-Clustering with Moving Costs, at which a learner maintains a set of k facilities over T rounds so as to minimize the connection cost of an adversarially selected sequence of clients. The ...

Daily manipulation tasks are characterized by regular features associated with the task structure, which can be described by multiple geometric primitives related to actions and object shapes. Only using Cartesian coordinate systems cannot fully represent ...

A strategic roadmap for noncarbonized fuels is a global priority, and the reduction of carbon dioxide emissions is a key focus of the Paris Agreement to mitigate the effects of rising temperatures. In this context, hydrogen is a promising noncarbonized fue ...

In this paper, we consider electric vehicle charging facilities that offer various levels of service, i.e., charging rates, for varying prices such that rational users choose a level of service that minimizes the total cost to themselves including an oppor ...

Time has always been a central factor in understanding the challenges of daily mobility. For a long time, and still today, methods of economic evaluation of transport projects have monetized time savings so that they can be included in the cost–benefit ana ...

We introduce contextual stochastic bilevel optimization (CSBO) -- a stochastic bilevel optimization framework with the lower-level problem minimizing an expectation conditioned on some contextual information and the upper-level decision variable. This fram ...

This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions ...

ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...

With the current trend of increasing complexity of industrial systems, the construction and monitoring of health indicators becomes even more challenging. Given that health indicators are commonly employed to predict the end of life, a crucial criterion fo ...

K-means is one of the fundamental unsupervised data clustering and machine learning methods. It has been well studied over the years: parallelized, approximated, and optimized for different cases and applications. With increasingly higher parallelism leadi ...

Benchmarking of scATAC-seq protocols demonstrates the effects of data quality on downstream analyses. ...

Last-mile delivery in the logistics chain contributes to congestion in urban networks due to frequent stops. Crowd-shipping is a sustainable and low-cost alternative to traditional delivery but relies heavily on the availability of occasional couriers. In ...

We generalize the celebrated results of Bernhard Riemann and Gaston Darboux: we give necessary and sufficient conditions for a bilinear form to be flat. More precisely, we give explicit necessary and sufficient conditions for a tensor field of type (0, 2) ...

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

Coverage-guided greybox fuzzers rely on control-flow coverage feedback to explore a target program and uncover bugs. Compared to control-flow coverage, data-flow coverage offers a more fine-grained approximation of program behavior. Data-flow coverage capt ...

Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...

Effective fall-detection and classification systems are vital in mitigating severe medical and economical consequences of falls to people in the fall risk groups. One class of such systems is based on wearable sensors. While there is a vast amount of acade ...

Coordinate Descent with Bandit Sampling

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Vehicle Trajectory Dataset from Drone-Collected Data at Three Swiss Roundabouts

Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling

Planetary-Scale Byzantine Fault Tolerance

Efficient Online Clustering with Moving Costs

A geometric optimal control approach for imitation and generalization of manipulation skills

Updates on Hydrogen Value Chain: A Strategic Roadmap

Sensitivity to user mischaracterizations in electric vehicle charging

Appropriations and Uses of Travel Time

Contextual Stochastic Bilevel Optimization

Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm

Hardware-Software co-design Methodologies for Edge AI Optimization

Learning Linearized Degradation of Health Indicators using Deep Koopman Operator Approach

Improving K-means Clustering Using Speculation

Systematic benchmarking of single-cell ATAC-sequencing protocols

A continuum approximation approach to the depot location problem in a crowd-shipping system

Bernhard Riemann 1861 revisited: existence of flat coordinates for an arbitrary bilinear form

A note on universal inference

DatAFLow: Toward a Data-Flow-Guided Fuzzer

Text Representation Learning for Low Cost Natural Language Understanding

Classification of fall directions via wearable motion sensors