Microsoft Office 2010 Beta released for public download

Top Ten Benefits of Office 2010 Beta

Express your ideas more visually
Office 2010 opens up a world of design options to help you give life to your ideas. The new and improved picture formatting tools such as color saturation and artistic effects let you transform your document visuals into a work of art. Combined with a wide range of new pre-built Office themes and SmartArt® graphic layouts, Office 2010 gives you more ways to make your ideas stick.

Accomplish more when working together
Brainstorm ideas, provide better version control, and meet deadlines faster when you work in groups. The co-authoring experience for Microsoft® Word 2010, Microsoft PowerPoint 2010, Microsoft® Excel Web App and Microsoft OneNote shared notebooks let you work on a file with several people at once - even from different locations.

Enjoy the familiar Office experience from more locations and more devices
With Office 2010, you can get things done more easily, from more locations and more devices. Using a smartphone or virtually any computer with an Internet connection, you can work when and where you want to work.

Microsoft Office Web Apps
Extend your Office 2010 experience to the Web. Store your Word, Excel, PowerPoint, and OneNote files online and then access, view, edit, and share content through the web.

Microsoft Office Mobile 2010
Stay current and respond quickly using enhanced mobile versions of Office 2010 applications, specifically suited to your Windows Mobile-based smartphone.

Create powerful data insights and visuals
Track and highlight important trends with new data analysis and visualization features in Excel 2010. The new Sparklines feature delivers a clear and compact visual representation of your data with small charts within worksheet cells. Filter and segment your PivotTable data in multiple layers using Slicers to spend more time analyzing and less time formatting.

Deliver compelling presentations
Captivate your audience with personalized videos in your presentation. Insert and customize videos directly in PowerPoint 2010—trim, add fades and effects, or bookmark key points in the video to call attention to selected scenes. Videos you insert are now embedded by default, relieving you from managing and sending additional video files.

Manage large volumes of e-mail with ease
Compress your long e-mail threads into a few conversations that can be categorized, filed, ignored, or cleaned up. The new Quick Steps feature let you perform multi-command tasks, such as reply and delete an e-mail in a single click, saving you time and in-box space.

Store and track all your ideas and notes in one place
Get the ultimate digital notebook for tracking, organizing, and sharing your text, picture, video and audio notes with OneNote 2010. New features such as version tracking, automatic highlighting, and Linked Notes give you more control over your notes so you’re always on top of where your ideas came from and the latest changes when working in teams.

Get your message out instantly
Broadcast your PowerPoint presentation to a remote audience, whether or not they have PowerPoint installed.5 The new Broadcast Slide Show feature allows you to share your presentation through a web browser quickly without additional set up.

Get things done faster and easier
Microsoft Office Backstage™ view replaces the traditional File menu to give you a centralized space for all of your file management tasks, such as the ability to save, share, print, and publish. The enhanced Ribbon across Office 2010 applications lets you access commands quickly and customize tabs to personalize the experience to your work style.

Access work across devices and platforms
Enjoy the freedom of using Office 2010 from more locations on more devices. When you use Microsoft® Office 2010, you’re getting the familiar and intuitive Office experience across PCs, Smartphones, and Web browsers on the go.

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KDD 2015 Best Research Paper Award “Algorithms for Public Private Social Networks”

Posted by Posted by Corinna Cortes, Head, Google Research NY

The 21st ACM conference on Knowledge Discovery and Data Mining (KDD’15), a main venue for academic and industry research in data management, information retrieval, data mining and machine learning, was held last week in Sydney, Australia. In the past several years, Google has been actively participating in KDD, with several Googlers presenting work at the conference in the research and industrial tracks. This year Googlers presented 12 papers at KDD (listed below, with Googlers in blue), all of which are freely available at the ACM Digital Library.

One of these papers, Efficient Algorithms for Public-Private Social Networks, co-authored by Googlers Ravi Kumar, Silvio Lattanzi, Vahab Mirrokni, former Googler intern Alessandro Epasto and research visitor Flavio Chierichetti, was awarded Best Research Paper. The inspiration for this paper comes from studying social networks and the importance of addressing privacy issues in analyzing such networks.

Privacy issues dictate the way information is shared among the members of the social network. In the simplest case, a user can mark some of her friends as private; this would make the connections (edges) between this user and these friends visible only to the user. In a different instantiation of privacy, a user can be a member of a private group; in this case, all the edges among the group members are to be considered private. Thus, each user in the social network has her own view of the link structure of the network. These privacy issues also influence the way in which the network itself can be viewed and processed by algorithms. For example, one cannot use the list of private friends of user X for suggesting potential friends or public news items to another user on the network, but one can use this list for the purpose of suggesting friends for user X.

As a result, enforcing these privacy guarantees translates to solving a different algorithmic problem for each user in the network, and for this reason, developing algorithms that process these social graphs and respect these privacy guarantees can become computationally expensive. In a recent study, Dey et al. crawled a snapshot of 1.4 million New York City Facebook users and reported that 52.6% of them hid their friends list. As more users make a larger portion of their social neighborhoods private, these computational issues become more important.

Motivated by the above, this paper introduces the public-private model of graphs, where each user (node) in the public graph has an associated private graph. In this model, the public graph is visible to everyone, and the private graph at each node is visible only to each specific user. Thus, any given user sees their graph as a union of their private graph and the public graph.

From algorithmic point of view, the paper explores two powerful computational paradigms for efficiently studying large graphs, namely, sketching and sampling, and focuses on some key problems in social networks such as similarity ranking, and clustering. In the sketching model, the paper shows how to efficiently approximate the neighborhood function, which in turn can be used to approximate various notions of centrality scores for each node - such centrality scores like the PageRank score have important applications in ranking and recommender systems. In the sampling model, the paper focuses on all-pair shortest path distances, node similarities, and correlation clustering, and develop algorithms that computes these notions on a given public-private graph and at the same time. The paper also illustrates the effectiveness of this model and the computational efficiency of the algorithms by performing experiments on real-world social networks.

The public-private model is an abstraction that can be used to develop efficient social network algorithms. This work leaves a number of open interesting research directions such as: obtaining efficient algorithms for the densest subgraph/community detection problems, influence maximization, computing other pairwise similarity scores, and most importantly, recommendation systems.

KDD’15 Papers, co-authored by Googlers:

Efficient Algorithms for Public-Private Social Networks (Best Paper Award)
Flavio Chierichetti, Alessandro Epasto, Ravi Kumar, Silvio Lattanzi, Vahab Mirrokni

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC
Sungjin Ahn, Anoop Korattikara, Nathan Liu, Suju Rajan, Max Welling

TimeMachine: Timeline Generation for Knowledge-Base Entities
Tim Althoff, Xin Luna Dong, Kevin Murphy, Safa Alai, Van Dang, Wei Zhang

Algorithmic Cartography: Placing Points of Interest and Ads on Maps
Mohammad Mahdian, Okke Schrijvers, Sergei Vassilvitskii

Stream Sampling for Frequency Cap Statistics
Edith Cohen

Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams
Nan Du, Mehrdad Farajtabar, Amr Ahmed, Alexander J.Smola, Le Song

Adaptation Algorithm and Theory Based on Generalized Discrepancy
Corinna Cortes, Mehryar Mohri, Andrés Muñoz Medina (now at Google)

Estimating Local Intrinsic Dimensionality
Laurent Amsaleg, Oussama Chelly, Teddy Furon, Stéphane Girard, Michael E. Houle Ken-ichi Kawarabayashi, Michael Nett

Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation
Chia-Tung Kuo, Xiang Wang, Peter Walker, Owen Carmichael, Jieping Ye, Ian Davidson

Going In-depth: Finding Longform on the Web
Virginia Smith, Miriam Connor, Isabelle Stanton

Annotating needles in the haystack without looking: Product information extraction from emails
Weinan Zhang, Amr Ahmed, Jie Yang, Vanja Josifovski, Alexander Smola

Focusing on the Long-term: Its Good for Users and Business
Diane Tang, Henning Hohnhold, Deirdre OBrien

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Public Key Cryptography Computation Cash and John Nash

This Thursday Associate Professor Steven Galbraith, a leading researcher in computational number theory and the mathematics of public key cryptography, will give a free public lecture at the University of Auckland. Steven has published over 50 papers in this area, written one book, and edited three conference proceedings. He has a Bachelors degree from the University of Waikato, a Masters from Georgia Tech in Atlanta, and he completed his PhD at Oxford University in 1996. He has had post-doc or visiting researcher positions at Royal Holloway University of London (UK), British Telecom Research (Ipswich, UK), University of Waterloo (Canada), Institute for Experimental Mathematics (Essen, Germany), University of Bristol (UK) and Hewlett-Packard Research Labs (Bristol, UK). He has been at the University of Auckland since 2009.
The lecture titled "Public Key Cryptography: Computation, Cash and John Nash" will explain how security can be enhanced by the use of hard computational problems from Mathematics. This was the basis for the creation of publi c key cryptography in the 1970s. Public key cryptography has many applications in information security, such as secure internet shopping, digital signatures and secure automatic software updates. We will see how digital signatures have now become a crucial component of the electronic currency bitcoin. Cryptography is, of course, of great interest to national security. Recently (only declassified in 2012) it has been revealed that John Nash (subject of the film A Beautiful Mind) sent a letter to the United States National Security Agency in 1955. His letter outlined new concepts that anticipated by decades fundamental notions in computational complexity and modern cryptography.
When: 6pm (free refreshments) for 6.30pm start, Thursday 15th May, 2014
Where: Owen G Glenn Building, Room OGGB3/260-092

Note that there is public parking in the basement of the Owen G Glenn Building at 12 Grafton Road.



from The Universal Machine http://universal-machine.blogspot.com/

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