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You know CHT for lines. Monotonic queues handle sliding window min/max in O(1) per query.
Covered with full walkthrough in this section.
Covered with full walkthrough in this section.
Understanding the property
Covered with full walkthrough in this section.
Covered with full walkthrough in this section.
Classic monotonic deque + DP. Requires maintaining min/max in sliding window while computing optimal splits.
Sliding window DP optimization. Teaches converting absolute value costs into monotonic deque queries.
DP with segment removal. Monotonic queue maintains optimal previous states within window.
Counting with monotonic structure. Foundation for deque-based DP optimization.
Foundation problem for monotonic deque. Must master this before DP optimization variants.
Monotonic deque on prefix sums. Handles negative numbers unlike sliding window approaches.
Direct DP + monotonic deque. dp[i] = max(dp[j]) + nums[i] for j in window, classic pattern.
Clean monotonic deque DP. Optimal value within k-window directly maps to deque maximum.
Multi-segment DP with sliding window preprocessing. Good bridge to harder window DP.
