When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

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Leaf-feeding insects trigger high-amplitude, defense-inducing electrical signals called slow wave potentials (SWPs). These signals are thought to be triggered by the long-distance transport of low molecular mass elicitors termed Ricca's factors. We sought ...

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer. Virtually all women with DCIS are treated, despite evidence suggesting up to half would remain with stable, non-threatening, disease. Overtreatment thus presents a press ...

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

The NA62 experiment at CERN, designed to study the ultra-rare decay K+ -> pi(+) nu(nu) over bar, has also collected data in beam-dump mode. In this configuration, dark photons may be produced by protons dumped on an absorber and reach a decay volume beginn ...

In this study, we map different types of channel geomorphic units in a sediment-starved, residual-flow reach before and after an artificial flood. Bedload particles of a previous sediment augmentation measure are tracked with passive integrated transponder ...

Neural network approaches to approximate the ground state of quantum hamiltonians require the numerical solution of a highly nonlinear optimization problem. We introduce a statistical learning approach that makes the optimization trivial by using kernel me ...

Ridesourcing has driven a lot of attention in recent years with the expansion of companies like Uber, Lift, and many others around the world. Companies use mobile applications connected through the internet to match drivers and their passengers real-time. ...

Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

Investigating the intangible nature of a cultural domain can take multiple forms, addressing for example the aesthetic, epistemic and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance as it c ...

Intelligent Fault Diagnosis (IFD) based on deep learning has proven to be an effective and flexible solution, attracting extensive research. Deep neural networks can learn rich representations from vast amounts of representative labeled data for various ap ...

This study investigates the use of a low cost microphone combined with state-of-the-art machine learning (ML) algorithms as online process monitoring to differentiate various materials and process regimes of Laser-Powder Bed Fusion (LPBF). Three processing ...

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

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Ricca's factors as mobile proteinaceous effectors of electrical signaling

TGF beta-mediated MMP13 secretion drives myoepithelial cell dependent breast cancer progression

Universal and adaptive methods for robust stochastic optimization

Search for dark photon decays to μ+μ- at NA62

Influence of channel geomorphic units on bedload transport and river morphology during low‐magnitude bed‐forming floods coupled with sediment augmentation

Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Modeling and Optimization of Ridesplitting Operations

Machine Learning Security in Industry: A Quantitative Survey

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-Driven Cultural Contact Detection Approach

Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis

Differentiation of materials and laser powder bed fusion processing regimes from airborne acoustic emission combined with machine learning