In preparation for cookie season, the late-night bakery is offering Insomniacs warm, indulgent flavors.

Centre County’s pre-eminent classical ballet school’s annual production of "The Nutcracker" will transport audiences to a magical world where life-sized toy soldiers fight giant mice, snowflakes dance, and the Sugar Plum Fairy welcomes all to the Nutcracker’s Kingdom from the Land of Sweets. 

The McKee Foods brand’s 2024 Christmas lineup includes a pair of new items and several returning products.

The Food Processing Suppliers Association (FPSA) today released its slate of packaging sessions as part of the PROCESS EXPO UNIVERSITY educational program taking place at Chicago's McCormick Place from September 15-18, 2015.

A conversation with the Oracle Weblogic Server product management team about community involvement in WebLogic's evolution.

A discussion of the relationship between Oracle Weblogic 12c and Oracle Virtual Assembly Builder.

A conversation about Oracle WebLogic 12c's role in the evolution of Oracle Fusion Middleware, plus a quick overview of product information resources.

Season 2, Act I of "Arcane," the animated series based on the popular multiplayer online battle arena game League of Legends, also had a strong debut, taking second place with 6.3M views.

Asia's 'unwanted children' crave 'hope more than anything else' at Christmas, says mission leader

The British pop star’s official 2016 calendar has arrived.

Consider an unknown smooth function $f: [0,1]^d ightarrow mathbb{R}$, and assume we are given $n$ noisy mod 1 samples of $f$, i.e., $y_i = (f(x_i) + eta_i) mod 1$, for $x_i in [0,1]^d$, where $eta_i$ denotes the noise. Given the samples $(x_i,y_i)_{i=1}^{n}$, our goal is to recover smooth, robust estimates of the clean samples $f(x_i) mod 1$. We formulate a natural approach for solving this problem, which works with angular embeddings of the noisy mod 1 samples over the unit circle, inspired by the angular synchronization framework. This amounts to solving a smoothness regularized least-squares problem -- a quadratically constrained quadratic program (QCQP) -- where the variables are constrained to lie on the unit circle. Our proposed approach is based on solving its relaxation, which is a trust-region sub-problem and hence solvable efficiently. We provide theoretical guarantees demonstrating its robustness to noise for adversarial, as well as random Gaussian and Bernoulli noise models. To the best of our knowledge, these are the first such theoretical results for this problem. We demonstrate the robustness and efficiency of our proposed approach via extensive numerical simulations on synthetic data, along with a simple least-squares based solution for the unwrapping stage, that recovers the original samples of $f$ (up to a global shift). It is shown to perform well at high levels of noise, when taking as input the denoised modulo $1$ samples. Finally, we also consider two other approaches for denoising the modulo 1 samples that leverage tools from Riemannian optimization on manifolds, including a Burer-Monteiro approach for a semidefinite programming relaxation of our formulation. For the two-dimensional version of the problem, which has applications in synthetic aperture radar interferometry (InSAR), we are able to solve instances of real-world data with a million sample points in under 10 seconds, on a personal laptop.

The United Nations agency for Palestinian refugees (UNRWA) launched an emergency coronavirus appeal Friday, saying Palestinians across the Middle East were suffering a devastating socio-economic impact.

Each year, the HARMAN team returns to the annual Consumer Electronics Show in Las Vegas to introduce best-in-class products and solutions that will transform key industries like automotive, audio and technology. Earlier this year at the Hard Rock Hotel &...

According to Samsung, the phone will be released on February 14 for $1,380 - several hundred dollars more than Apple's most expensive iPhone 11 Pro model. It will be available on