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原创 [leetcode] House Robber III

The thief has found himself a new place for his thievery again. There is only one entrance to this area, called the "root." Besides the root, each house has one and only one parent house. After a tour

2016-04-24 11:09:38 295

原创 [leetcode] Dungeon game

The demons had captured the princess (P) and imprisoned her in the bottom-right corner of a dungeon. The dungeon consists of M x N rooms laid out in a 2D grid. Our valiant knight (K) was initially pos

2016-01-26 06:35:04 298

原创 [Leetcode] Maximum Product Subarray

Find the contiguous subarray within an array (containing at least one number) which has the largest product.For example, given the array [2,3,-2,4], the contiguous subarray [2,3] has the largest pro

2016-01-18 04:17:04 275

原创最大流 Ford Fulkerson, EK, SAP

1. Ford-Fulkerson 方法中，有三个概念：剩余网络，增广路径，割。称Ford-Fulkerson为方法而不是算法是因为它是一类算法的统称。剩余网络，就是在原网络中增加反向边。如果选择从点u到点v流过流量f，那从v到u就有容量为f的反向边。反向边存在的意义是对已经选择的流“反悔”，如下图，如果第一次选择路径0-1-3-5，那第二次就没有路径可选了，此时流量为1。

2015-10-28 03:39:01 523

原创强连通分量 Kosaraju算法

强连通分量 Kosaraju算法伪代码(摘自Introduction to Algorithm 3rd Edition)：Strongly_connected_components( G )1. call DFS(G) to compute finishing time u.f for each vertex u2. compute GT3. call DFS(GT), bu

2015-10-24 11:27:56 647

Probabilistic Inference Using MCMC

Markov chain Monte Carlo (MCMC) methods (which include random walk Monte Carlo methods) are a class of algorithms for sampling from probability distributions based on constructing a Markov chain that has the desired distribution as its equilibrium distribution. The state of the chain after a large number of steps is then used as a sample of the desired distribution. The quality of the sample improves as a function of the number of steps. -Wiki

2012-12-09

Data Structures and Algorithms for Big Databases

I/O model and cache-oblivious analysis Write-optimized data structures How write-optimized data structures can help file systems Block-replacement algorithms Indexing strategies Log-structured merge trees Bloom filters

2012-12-09

随机过程-Stochastic Processes

In probability theory, a stochastic process , or sometimes random process (widely used) is a collection of random variables; this is often used to represent the evolution of some random value, or system, over time. This is the probabilistic counterpart to a deterministic process (or deterministic system). Instead of describing a process which can only evolve in one way (as in the case, for example, of solutions of an ordinary differential equation), in a stochastic or random process there is some indeterminacy: even if the initial condition (or starting point) is known, there are several (often infinitely many) directions in which the process may evolve. -Wiki

2012-12-09

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原创 [leetcode] House Robber III

原创 [leetcode] Dungeon game

原创 [Leetcode] Maximum Product Subarray

原创 最大流 Ford Fulkerson, EK, SAP

原创 强连通分量 Kosaraju算法

Probabilistic Inference Using MCMC

Data Structures and Algorithms for Big Databases

随机过程-Stochastic Processes

空空如也

原创最大流 Ford Fulkerson, EK, SAP

原创强连通分量 Kosaraju算法