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Ayatollah Khamenei doubles down on Iran's commitment not to engage in talks with the United States; Trey Yingst reports. The drone was reportedly hit in the early morning at the port city of Mahshahr, which is in the oil-rich Khuzestan province and lies on the Persian Gulf. "The downed droned definitely belonged to a foreign country. Its wreckage has been recovered and is being investigated," the governor of Khuzestan, Gholamreza Shariati, said, according to the official IRNA news agency. He said the drone violated Iran's airspace but did not provide any additional information, including whether it was a military or civilian drone.

Recurrent Neural Networks (RNNs) can be seriously impacted by the initial parameters assignment, which may result in poor generalization performances on new unseen data. With the objective to tackle this crucial issue, in the context of RNN based classification, we propose a new supervised layer-wise pretraining strategy to initialize network parameters. The proposed approach leverages a data-aware strategy that sets up a taxonomy of classification problems automatically derived by the model behavior. To the best of our knowledge, despite the great interest in RNN-based classification, this is the first data-aware strategy dealing with the initialization of such models. The proposed strategy has been tested on four benchmarks coming from two different domains, i.e., Speech Recognition and Remote Sensing. Results underline the significance of our approach and point out that data-aware strategies positively support the initialization of Recurrent Neural Network based classification models.

NEW DELHI: India on Friday sought to add meat to its strategic partnership with Germany by wooing industries to invest in defence corridors of Tamil Nadu and Uttar Pradesh. At their biennial summit in New Delhi, India and Germany also sought to give momentum to revive stalled negotiations for free-trade agreement with the European Union. Proposed in 2007, the negotiations hit a roadblock in 2013 when the two sides arrived at an impasse on tariffs and market access. Disagreements on standards and practices exacerbated the situation and negotiations were shelved for five years. Germany has been an advocate of the deal and welcomed the resumption of negotiations last year.

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We present local ensembles, a method for detecting extrapolation at test time in a pre-trained model. We focus on underdetermination as a key component of extrapolation: we aim to detect when many possible predictions are consistent with the training data and model class. Our method uses local second-order information to approximate the variance of predictions across an ensemble of models from the same class. We compute this approximation by estimating the norm of the component of a test point's gradient that aligns with the low-curvature directions of the Hessian, and provide a tractable method for estimating this quantity. Experimentally, we show that our method is capable of detecting when a pre-trained model is extrapolating on test data, with applications to out-of-distribution detection, detecting spurious correlates, and active learning.

Massive volumes of high-dimensional data that evolves over time is continuously collected by contemporary information processing systems, which brings up the problem of organizing this data into clusters, i.e. achieve the purpose of dimensional deduction, and meanwhile learning its temporal evolution patterns. In this paper, a framework for evolutionary subspace clustering, referred to as LSTM-ESCM, is introduced, which aims at clustering a set of evolving high-dimensional data points that lie in a union of low-dimensional evolving subspaces. In order to obtain the parsimonious data representation at each time step, we propose to exploit the so-called self-expressive trait of the data at each time point. At the same time, LSTM networks are implemented to extract the inherited temporal patterns behind data in an overall time frame. An efficient algorithm has been proposed based on MATLAB. Next, experiments are carried out on real-world datasets to demonstrate the effectiveness of our proposed approach. And the results show that the suggested algorithm dramatically outperforms other known similar approaches in terms of both run time and accuracy.

A fully autonomous ship tracing the journey of the Mayflower is being built by a UK-based team, with help from tech firm IBM. The Mayflower Autonomous Ship, or MAS, will launch from Plymouth in the UK in September 2020. Its voyage will mark the 400th anniversary of the pilgrim ship which brought European settlers to America in 1620. IBM is providing artificial intelligence systems for the ship. The vessel will make its own decisions on its course and collision avoidance, and will even make expensive satellite phone calls back to base if it deems it necessary.

A fully autonomous ship tracing the journey of the Mayflower is being built by a UK-based team, with help from tech firm IBM. The Mayflower Autonomous Ship, or MAS, will launch from Plymouth in the UK in September 2020. Its voyage will mark the 400th anniversary of the pilgrim ship which brought European settlers to America in 1620. IBM is providing artificial intelligence systems for the ship. The vessel will make its own decisions on its course and collision avoidance, and will even make expensive satellite phone calls back to base if it deems it necessary.

Fox News Flash top headlines for Oct. 14 are here. Check out what's clicking on Foxnews.com Attacking enemy lines as a heavily up-gunned armored robot, firing lasers, knocking enemy drones out of the air with "elevating" weapons, controlling air and ground drones as networked "nodes" in war and using AI to organize long-range targeting data -- are all desired attributes for the Army's new infantry vehicle - the Optionally Manned Fighting Vehicle. The new vehicle, slated to ultimately replace the decades-old Bradley, will achieve operational combat status as soon as 2026 -- and, according to Army documents, pave the way forward into a new era of major, high-powered, mechanized warfare. As it enters a new prototyping and test phase for the vehicle, the Army is further refining its ambitious and high-standard requirements.