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This is a practical guide to P-splines, a simple, flexible and powerful tool for smoothing. P-splines combine regression on B-splines with simple, discrete, roughness penalties. They were introduced by the authors in 1996 and have been used in many diverse applications. The regression basis makes it straightforward to handle non-normal data, like in generalized linear models. The authors demonstrate optimal smoothing, using mixed model technology and Bayesian estimation, in addition to classical tools like cross-validation and AIC, covering theory and applications with code in R. Going far beyond simple smoothing, they also show how to use P-splines for regression on signals, varying-coefficient models, quantile and expectile smoothing, and composite links for grouped data. Penalties are the crucial elements of P-splines; with proper modifications they can handle periodic and circular data as well as shape constraints. Combining penalties with tensor products of B-splines extends these attractive properties to multiple dimensions. An appendix offers a systematic comparison to other smoothers.
Google’s Legal Department addresses cutting-edge issues that run from driverless cars to green-energy power cables for the Eastern Seaboard and legal hot spots from China to Turkey. Our legal department today consists of more than 900 legal team members, a significant growth from the one lawyer that made up the legal department in 2001. The unique culture of Google itself has inspired the legal department to innovate in ways that are more progressive than most companies of a similar size. The Google Legal Team supports the vision of the company’s engineers who are trying to create new technologies that will have an international impact on the lives of people. Accordingly, our legal team focuses its support on the interests of the users of the company’s technology and defends Google so that it can continue to focus on the company vision.
The blockchain industry has recently broken through into the general public’s consciousness. Gone were the days of blockchain projects being solely the interest of computer programmers, libertarians, and anti-government activists. Now, discussion of the industry graced the pages of the New York Times1 and the Wall Street Journal,2 and the nascent industry was regularly covered by television news programs such as CNBC’s Fast Money.3 The majority of this attention was directed to price increases in cryptocurrencies, such as Bitcoin, but a new vehicle for raising capital – known as an initial coin offering, or ICO – also fueled public enthusiasm. All of this excitement and curiosity has made it harder and harder for lawyers to ignore this industry. As such, it is beneficial for lawyers to get a high-level understanding of what the blockchain industry is, and how it makes technologies like cryptocurrencies possible.
There are many categories of information that defy easy systematic computational analysis. Patents are not one of them. Ever since the earliest litterae patentes were granted by host countries to foreigners willing to share their knowledge with their hosts, the monopoly rights granted by governments have been meticulously documented. The richness of data detailing both the monopoly right to exclude – granted to a patent’s owner – and the patent document’s informational disclosure of how to make and use a claimed invention – intended to enrich the metaphorical storehouse of knowledge – has accumulated at an accelerating pace since the days of the first letters patent. So rapidly has the information embodied in patents grown that analytical techniques for sorting and computationally evaluating that information have always lagged far behind the deluge of accumulating data. In lieu of precise algorithmic methods for understanding the contents of patents, a specialized guild of patent attorneys has evolved to sell their largely subjective interpretations of what patents disclose, cover, and are worth. Since patent attorneys must pass a challenging patent bar exam, in addition to a state bar exam, their numbers are controlled, allowing their fees to be high. However, recent years have seen the inexorable rise of more objective, falsifiable, mathematical, and computational methods for analyzing patents. Progress in patent analytics has accelerated rapidly in recent years, democratizing, elucidating, and making more rigorous the interpretation of patent data.
Let me tell you a story, one that may sound familiar to you. Anna is preparing a termination agreement. This task takes her anywhere from one to four hours. That’s a lot of time to spend on what should be a simple contract, but each time she is asked to prepare one she runs into the same problems. She starts her work by asking human resources for information about the employee. Then she goes back and forth with emails, trying to track down all the bits and pieces she needs to create the agreement. She also has to contact multiple people: the equity plan administrator to find out if the employee has any stock grants; the safety manager to find out if there are any outstanding claims; and someone in finance to check for any promissory notes the employee has signed. Then, she goes back to HR to clarify all the information before she goes to chase down more.
Changes in the US Federal Rules of Civil Procedure in 2006 made electronic documents part of the evidence material for a case.1 This led to an “e-discovery revolution,” and natural language processing (NLP) technologies became standard tools in the document review process in civil litigation.2 This was welcome news for investigators and litigators, since nowadays the most interesting and substantial pieces of evidence are often contained in electronic documents, particularly email conversations. However, these legal changes coincided with the explosion of available data, and the sheer volume of electronic information has made it necessary to search for new ways to handle and review electronic information.3
The development of knowledge management and the early adoption of innovative technology into Littler Mendelson’s practice did not occur by chance, or as a reactionary response to “everyone else doing it.” Littler launched a robust and comprehensive knowledge management program and adopted new technology in order to support its long-term strategic plans, help achieve its vision of becoming a global law firm, and uphold its commitment to meeting clients’ needs. By making both knowledge management and technology adoption an integral part of the firm’s strategic plan, rather than an ad hoc response to episodic changes in the market, Littler has fully integrated both into the way the firm does business and serves its clients.
Technological advancements are improving how courts operate by changing the way they handle proceedings and interact with litigants. Court Innovations is a socially minded software startup that enables citizens, law enforcement, and courts to resolve legal matters through Matterhorn, an online communication and dispute resolution platform. Matterhorn was conceived at the University of Michigan Law School and successfully piloted in two Michigan district courts beginning in 2014. The platform now operates in over 40 courts and in at least eight states, and it has facilitated the resolution of more than 40,000 cases to date.2 These numbers will continue to grow as new categories of disputes and other legal matters become eligible for online management and resolution and as more court systems recognize the economic and social benefits of adopting online platform technology.3 This case study chronicles the development, implementation, and refinement of Matterhorn.
The justice system in the USA is modeled on that of the UK: The rule base is made up of common law derived from cases and statutes. The US system differs, though, because it is controlled by a written Constitution that sets out the operation of the courts and controls some of the core relationships between people and government. In all serious criminal cases where the government is the plaintiff, the accused are generally entitled by the Constitution to free representation by appointed lawyers. However, there is no corresponding constitutional right to representation by lawyers in civil cases.
When arguing before a judicial body, lawyers must support their legal arguments by citing prior court decisions that adopted similar reasoning or reached a similar conclusion. Finding such prior decisions is often a tedious and time-consuming process that requires many hours of reading through judicial opinions to determine if they are actually relevant, and then drawing parallels to those few decisions that are most relevant. Many attorneys employ paralegals and junior associates to conduct legal research on a full-time basis, so any system that makes it quicker and easier for attorneys to locate relevant cases and statutes can save enormous amounts of time and money.