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新闻的暗语

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亲切友好的交谈 —— 字面意思;
坦率交谈 —— 分歧很大,无法沟通;
交换了意见 —— 会谈各说各的,没有达成协议;
充分交换了意见 —— 双方无法达成协议,吵得厉害;
增进了双方的了解 —— 双方分歧很大;
会谈是有益的 —— 双方目标暂时相距甚远,能坐下来谈就很好;
我们持保留态度 —— 我们拒绝同意;
尊重 —— 不完全同意;
赞赏 —— 不尽同意;
遗憾 —— 不满;
不愉快 —— 激烈的冲突;
表示极大的愤慨 —— 现在我拿你没办法;
严重关切 —— 可能要干预;
不能置之不理 —— 即将干涉;
保留做出进一步反应的权利 —— 我们将报复;
我们将重新考虑这一问题的立场 —— 我们已经改变了原来的(友好)政策;
拭目以待 —— 最后警告;
请于X月X日前予以答复 —— X月X日后我们两国可能处于非和平状态;
由此引起的后果将由**负责 —— 可能的话我国将诉诸武力(这也可能是虚张声势的俗语);
这是我们万万不能容忍的 —— 战争在即;
这是不友好的行动 —— 这是敌视我们的行动,可能引起战争的行动;
是可忍孰不可忍 —— 不打算忍了,要动手了;
悬崖勒马 —— 想被XX么?
勿谓言之不预也 —— 我们要亮必杀了!

历史上,小白兔两次祭出必杀技“勿谓言之不预也”,分别是1962年9月22日《人民日报》社论《是可忍,孰不可忍》和1978年12月25日《人民日报》社论《我们的忍耐是有限度的》,对象分别是印度和越南。自韬光养晦发展经济之后还从未在正式场合使用过。

转载于凯迪社区,略有修改。

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Written by Weiwei

11/01/2012 at 14:54

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How the internet works? (for dummies)

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Written by Weiwei

08/10/2010 at 23:42

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这张照片是不是让你想起电影《狮子王》?

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Exclusiveplx

Written by Weiwei

18/08/2010 at 20:33

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Erfolgreich fern der Heimat

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Weiwei Cheng bei der PreisverleihungDoktorand des Marburger Fachbereichs Mathematik und Informatik erhält chinesische Auszeichnung

Weiwei Cheng, Doktorand am Marburger Fachbereich Mathematik und Informatik, hat den “Chinese Government Award for Outstanding Self-Financed Students Abroad” erhalten.

Chengs Forschungsschwerpunkt liegt im so genannten Präferenzlernen: Er entwickelt beispielsweise auf der Basis von gegebenen Daten und Beobachtungen über die bevorzugt besuchten Internetseiten einer Person Ranking-Modelle, mit deren Hilfe man dem Nutzer Alternativen zur Verfügung stellen kann. In seiner Ansprache, die Cheng bei der Preisverleihung in der chinesischen Botschaft in Berlin auch stellvertretend für die 36 weiteren Geehrten gab, dankte er seinem Marburger Mentor Professor Dr. Eyke Hüllermeier dafür, dass er “mich an das Forschungsfeld Maschinelles Lernen herangeführt hat”.

Hüllermeier lobt Fleiß und Ehrgeiz seines Doktoranden: “Er hat alles, was ein guter Wissenschaftler braucht, und kann seine Arbeiten sehr gut kommunizieren.”

Der mit 5000 Dollar dotierte Preis wird jährlich vom “China Scholarship Council” an chinesische Nachwuchswissenschaftler vergeben, die während ihres Graduiertenstudiums im Ausland überdurchschnittliche Leistungen erzielen und sich selbst finanzieren, also nicht von staatlicher Förderung abhängig sind.

Quelle: Pressestelle der Philipps-Universität Marburg
Update: Ein Artikel aus Oberhessische Presse

Written by Weiwei

21/07/2010 at 00:43

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The Most Important Algorithms (in CS and Math)

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我接触的同僚之中,大约每个人心里都有自己最爱的几种算法。下面是Christoph Koutschan列出来的32类计算机与数学领域最为重要的算法(按字符顺序排列)。覆盖的面很广,评价很精准。

  1. A* search algorithm
    Graph search algorithm that finds a path from a given initial node to a given goal node. It employs a heuristic estimate that ranks each node by an estimate of the best route that goes through that node. It visits the nodes in order of this heuristic estimate. The A* algorithm is therefore an example of best-first search.
  2. Beam Search
    Beam search is a search algorithm that is an optimization of best-first search. Like best-first search, it uses a heuristic function to evaluate the promise of each node it examines. Beam search, however, only unfolds the first m most promising nodes at each depth, where m is a fixed number, the beam width.
  3. Binary search
    Technique for finding a particular value in a linear array, by ruling out half of the data at each step.
  4. Branch and bound
    A general algorithmic method for finding optimal solutions of various optimization problems, especially in discrete and combinatorial optimization.
  5. Buchberger’s algorithm
    In computational algebraic geometry and computational commutative algebra, Buchberger’s algorithm is a method of transforming a given set of generators for a polynomial ideal into a Gröbner basis with respect to some monomial order. One can view it as a generalization of the Euclidean algorithm for univariate gcd computation and of Gaussian elimination for linear systems.
  6. Data compression
    Data compression or source coding is the process of encoding information using fewer bits (or other information-bearing units) than an unencoded representation would use through use of specific encoding schemes.
  7. Diffie-Hellman key exchange
    Cryptographic protocol which allows two parties that have no prior knowledge of each other to jointly establish a shared secret key over an insecure communications channel. This key can then be used to encrypt subsequent communications using a symmetric key cipher.
  8. Dijkstra’s algorithm
    Algorithm that solves the single-source shortest path problem for a directed graph with nonnegative edge weights.
  9. Discrete differentiation
    I.e., the formula f'(x) = (f(x+h) – f(x-h)) / 2h.
  10. Dynamic programming
    Dynamic programming is a method for reducing the runtime of algorithms exhibiting the properties of overlapping subproblems and optimal substructure, described below.
  11. Euclidean algorithm
    Algorithm to determine the greatest common divisor (gcd) of two integers. It is one of the oldest algorithms known, since it appeared in Euclid’s Elements around 300 BC. The algorithm does not require factoring the two integers.
  12. Expectation-maximization algorithm (EM-Training)
    In statistical computing, an expectation-maximization (EM) algorithm is an algorithm for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. EM alternates between performing an expectation step, which computes the expected value of the latent variables, and a maximization step, which computes the maximum likelihood estimates of the parameters given the data and setting the latent variables to their expectation.
  13. Fast Fourier transform (FFT)
    Efficient algorithm to compute the discrete Fourier transform (DFT) and its inverse. FFTs are of great importance to a wide variety of applications, from digital signal processing to solving partial differential equations to algorithms for quickly multiplying large integers.
  14. Gradient descent
    Gradient descent is an optimization algorithm that approaches a local minimum of a function by taking steps proportional to the negative of the gradient (or the approximate gradient) of the function at the current point. If instead one takes steps proportional to the gradient, one approaches a local maximum of that function; the procedure is then known as gradient ascent.
  15. Hashing
    A function for summarizing or probabilistically identifying data. Typically this means one applies a mathematical formula to the data, producing a string which is probably more or less unique to that data. The string is much shorter than the original data, but can be used to uniquely identify it.
  16. Heaps (heap sort)
    In computer science a heap is a specialized tree-based data structure. Heaps are favourite data structures for many applications: Heap sort, selection algorithms (finding the min, max or both of them, median or even any kth element in sublinear time), graph algorithms.
  17. Karatsuba multiplication
    For systems that need to multiply numbers in the range of several thousand digits, such as computer algebra systems and bignum libraries, long multiplication is too slow. These systems employ Karatsuba multiplication, which was discovered in 1962.
  18. LLL algorithm
    The Lenstra-Lenstra-Lovasz lattice reduction (LLL) algorithm is an algorithm which, given a lattice basis as input, outputs a basis with short, nearly orthogonal vectors. The LLL algorithm has found numerous applications in cryptanalysis of public-key encryption schemes: knapsack cryptosystems, RSA with particular
    settings, and so forth.
  19. Maximum flow
    The maximum flow problem is finding a legal flow through a flow network that is maximal. Sometimes it is defined as finding the value of such a flow. The maximum flow problem can be seen as special case of more complex network flow problems. The maximal flow is related to the cuts in a network by the Max-flow min-cut theorem. The Ford-Fulkerson algorithm computes the maximum flow in a flow network.
  20. Merge sort
    A sorting algorithm for rearranging lists (or any other data structure that can only be accessed sequentially, e.g. file streams) into a specified order.
  21. Newton’s method
    Efficient algorithm for finding approximations to the zeros (or roots) of a real-valued function. Newton’s method is also a well-known algorithm for finding roots of equations in one or more dimensions. It can also be used to find local maxima and local minima of functions.
  22. Q-learning
    Q-learning is a reinforcement learning technique that works by learning an action-value function that gives the expected utility of taking a given action in a given state and following a fixed policy thereafter. A strength with Q-learning is that it is able to compare the expected utility of the available actions without requiring a model of the environment.
  23. Quadratic sieve
    The quadratic sieve algorithm (QS) is a modern integer factorization algorithm and, in practice, the second fastest method known (after the number field sieve, NFS). It is still the fastest for integers under 110 decimal digits or so, and is considerably simpler than the number field sieve.
  24. RANSAC
    RANSAC is an abbreviation for “RANdom SAmple Consensus”. It is an algorithm to estimate parameters of a mathematical model from a set of observed data which contains “outliers”. A basic assumption is that the data consists of “inliers”, i. e., data points which can be explained by some set of model parameters, and “outliers” which are data points that do not fit the model.
  25. RSA
    Algorithm for public-key encryption. It was the first algorithm known to be suitable for signing as well as encryption. RSA is still widely used in electronic commerce protocols, and is believed to be secure given sufficiently long keys.
  26. Schönhage-Strassen algorithm
    In mathematics, the Schönhage-Strassen algorithm is an asymptotically fast method for multiplication of large integer numbers. The run-time is O(N log(N) log(log(N))). The algorithm uses Fast Fourier Transforms in rings.
  27. Simplex algorithm
    In mathematical optimization theory, the simplex algorithm a popular technique for numerical solution of the linear programming problem. A linear programming problem consists of a collection of linear inequalities on a number of real variables and a fixed linear functional which is to be maximized (or minimized).
  28. Singular value decomposition (SVD)
    In linear algebra, SVD is an important factorization of a rectangular real or complex matrix, with several applications in signal processing and statistics, e.g., computing the pseudoinverse of a matrix (to solve the least squares problem), solving overdetermined linear systems, matrix approximation, numerical weather prediction.
  29. Solving a system of linear equations
    Systems of linear equations belong to the oldest problems in mathematics and they have many applications, such as in digital signal processing, estimation, forecasting and generally in linear programming and in the approximation of non-linear problems in numerical analysis. An efficient way to solve systems of linear equations is given by the Gauss-Jordan elimination or by the Cholesky decomposition.
  30. Strukturtensor
    In pattern recognition: Computes a measure for every pixel which tells you if this pixel is located in a homogenous region, if it belongs to an edge, or if it is a vertex.
  31. Union-find
    Given a set of elements, it is often useful to partition them into a number of separate, nonoverlapping groups. A disjoint-set data structure is a data structure that keeps track of such a partitioning. A union-find algorithm is an
    algorithm that performs two useful operations on such a data structure:
    Find: Determine which group a particular element is in.
    Union: Combine or merge two groups into a single group.
  32. Viterbi algorithm
    Dynamic programming algorithm for finding the most likely sequence of hidden states – known as the Viterbi path – that result in a sequence of observed events, especially in the context of hidden Markov models.
Daniel Lemire在看到这个名单之后,列出了他心中的Top 5:
  • Binary search is the first non-trivial algorithm I remember learning.
  • The Fast Fourier transform (FFT) is an amazing algorithm. Combined with the convolution theorem, it lets you do magic.
  • While hashing is not an algorithm, it is one of the most powerful and useful idea in Computer Science. It takes minutes to explain it, but years to master.
  • Merge sort is the most elegant sorting algorithm. You can explain it in three sentences to anyone.
  • While not an algorithm per se, the Singular Value Decomposition (SVD) is the most important Linear Algebra concept I don’t remember learning as an undergraduate. (And yes, I went to a good school. And yes, I was an A student.) It can help you invert singular matrices and do other similar magic.

Written by Weiwei

17/07/2010 at 14:10

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Top 10 Stop Motion Videos on YouTube

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The video above "DEADLINE post-it stop motion" is one of them. It has already drew 3,858,368 views by now. The other videos are listed at Mashable.

Written by Weiwei

18/06/2010 at 16:10

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Google有多少服务器?

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via gizmodo

It’s said that 2% of all the servers in the world belong to Google.
Click the picture for a closer look.

Written by Weiwei

15/04/2010 at 21:59

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