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Identifying multitarget impurities on contact lenses is challenging because traditional methods such as polymerase chain reaction cannot be used on the unknown target. Other sampling methods often require expensive antibodies or dyes. Therefore, this resea ...
As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...
We study generalization properties of random features (RF) regression in high dimensions optimized by stochastic gradient descent (SGD) in under-/overparameterized regime. In this work, we derive precise non-asymptotic error bounds of RF regression under b ...
As modern machine learning continues to achieve unprecedented benchmarks, the resource demands to train these advanced models grow drastically. This has led to a paradigm shift towards distributed training. However, the presence of adversariesâwhether ma ...
Following the conceptual design, the engineering design of the dc magnet and cable-in-conduit conductor (CICC) for the Super-X test facility has been done in 2021. Totally three types of conductors with different structures were designed for the three pair ...
In motor-related brain regions, movement intention has been successfully decoded from invivo spike train by isolating a lower-dimension manifold that the high-dimensional spiking activity is constrained to. The mechanism enforcing this constraint remains u ...
Caprock formations, such as shales, play a key role in safe underground CO2 storage since they serve as a hydromechanical barrier that prevents migration of the injected CO2 to the surface. While their hydromechanical response is important to ensure their ...
Data-driven and model-driven methodologies can be regarded as competitive fields since they tackle similar problems such as prediction. However, these two fields can learn from each other to improve themselves. Indeed, data-driven methodologies have been d ...
Low throughput is one of dissolution Dynamic Nuclear Polarization (dDNP) main shortcomings. Especially for clinical and preclinical applications, where direct 13C nuclei polarization is usually pursued, it takes hours to generate one single hyperpolarized ...
Estimation of causal effects using machine learning methods has become an active research field in econometrics. In this paper, we study the finite sample performance of meta-learners for estimation of heterogeneous treatment effects under the usage of sam ...
