Sentence examples for parallel decision from inspiring English sources

Nuno Amado et al. [14] presents an overview on the various ideas regarding implementing parallel decision trees using data parallelism, task parallelism and hybrid parallelism in their work.

In a parallel decision, Royal Caribbean shareholders voted today to adjourn their meeting.

It achieves additional 0.4 dB coding gain over 14tap parallel decision feedback decoder (PDFD) with 39% area reduction.

The FISA court has apparently made a parallel decision: since someone, somewhere, probably used a phone or e-mail in a way related to foreign intelligence, entire databases of calls and e-mails are relevant.

This referral to the "appropriate people" is as crucial as the parallel decision in the U.S. political process which baffles any foreign observer of American government the decision as to which committee or subcommittee of the Congress a certain bill is to be assigned.

There are other parallel decision tree learning algorithms [19, 21, 22] that work by clubbing data and task parallelism.

In two parallel decisions, dated Monday and delivered to the lawyers today, a four-justice panel of the Appellate Division in Brooklyn ruled unanimously that the state had acted illegally.

Commenting on the parallel decisions in Orange and Salt Lake City, Jon W. Davidson, a supervising lawyer with the Lambda Legal Defense and Education Fund, which represented students in both districts, said, "I think the message of both of these districts is it's a losing battle for school districts to try and prevent students from forming the clubs they want, including gay-straight alliances".

The United States is already collecting tariffs totaling about 30 percent while the European Union is expected to impose similar tariffs of about 50 percent on June 5, and may backdate them to March 5. Parallel decisions by the Obama administration and the European Union to separately negotiate high prices for imported solar panels may prove unpopular among environmentalists.

Initial research indicates that Tradeshift's data set may even improve parallel decision-making, a current weakness of machine learning.

Inspired by the concept of the 'two-level game' (Putnam, 1988) that captures parallel decision-making on domestic and international political spheres, these countries seem exposed to a more complex 'three-level game', where diplomatic interests towards countries of origin and destination compete alongside domestic interests.