Sliding Window Maximum | LeetCode



A long array A[] is given to you. There is a sliding window of size w which is moving from the very left of the array to the very right. You can only see the w numbers in the window. Each time the sliding window moves rightwards by one position. Following is an example:
The array is [1 3 -1 -3 5 3 6 7], and w is 3.
Removing redundant elements and storing only elements that need to be considered in the queue is the key to achieve the efficient O(n) solution below.
The above algorithm could be proven to have run time complexity of O(n). This is because each element in the list is being inserted and then removed at most once. Therefore, the total number of insert + delete operations is 2n.
Read full article from Sliding Window Maximum | LeetCode

No comments:

Post a Comment

Labels

Algorithm (219) Lucene (130) LeetCode (97) Database (36) Data Structure (33) text mining (28) Solr (27) java (27) Mathematical Algorithm (26) Difficult Algorithm (25) Logic Thinking (23) Puzzles (23) Bit Algorithms (22) Math (21) List (20) Dynamic Programming (19) Linux (19) Tree (18) Machine Learning (15) EPI (11) Queue (11) Smart Algorithm (11) Operating System (9) Java Basic (8) Recursive Algorithm (8) Stack (8) Eclipse (7) Scala (7) Tika (7) J2EE (6) Monitoring (6) Trie (6) Concurrency (5) Geometry Algorithm (5) Greedy Algorithm (5) Mahout (5) MySQL (5) xpost (5) C (4) Interview (4) Vi (4) regular expression (4) to-do (4) C++ (3) Chrome (3) Divide and Conquer (3) Graph Algorithm (3) Permutation (3) Powershell (3) Random (3) Segment Tree (3) UIMA (3) Union-Find (3) Video (3) Virtualization (3) Windows (3) XML (3) Advanced Data Structure (2) Android (2) Bash (2) Classic Algorithm (2) Debugging (2) Design Pattern (2) Google (2) Hadoop (2) Java Collections (2) Markov Chains (2) Probabilities (2) Shell (2) Site (2) Web Development (2) Workplace (2) angularjs (2) .Net (1) Amazon Interview (1) Android Studio (1) Array (1) Boilerpipe (1) Book Notes (1) ChromeOS (1) Chromebook (1) Codility (1) Desgin (1) Design (1) Divide and Conqure (1) GAE (1) Google Interview (1) Great Stuff (1) Hash (1) High Tech Companies (1) Improving (1) LifeTips (1) Maven (1) Network (1) Performance (1) Programming (1) Resources (1) Sampling (1) Sed (1) Smart Thinking (1) Sort (1) Spark (1) Stanford NLP (1) System Design (1) Trove (1) VIP (1) tools (1)

Popular Posts