For the abbreviation of recommend readings, see the Textbook section in the course page.
| Week | Date | Contents | Notes |
|---|---|---|---|
| 1 | May 26 (Tue) | Introduction and Asymptotic Analysis (KT 2.2, KT 2.4) | |
| May 28 (Thu) | Graph Basics (KT 3.1 - KT 3.6) | ||
| 2 | Jun 02 (Tue) | Greedy Algorithms: Box Packing and Interval Scheduling (KT 4.1) | HW1 & Task1 Deadline |
| Jun 04 (Thu) | Greedy Algorithms: Huffman Code (KT 4.8) | ||
| 3 | Jun 09 (Tue) | Divide and Conquer: Merge Sort and Counting Inversions (KT 5.1, KT 5.3) | HW2 Deadline |
| Jun 11 (Thu) | Divide and Conquer: Quick Sort and Selection (KT 13.5) | ||
| Jun 12 (Fri) | Mid-Exam (2 hours, to be completed within a 24-hour window) | ||
| 4 | Jun 16 (Tue) | Dynamic Programming: Subset Sum and LCS (KT 6.6) | HW3 & P1 Deadline |
| Jun 18 (Thu) | Dynamic Programming: Matrix Chain Multiplication | ||
| 5 | Jun 23 (Tue) | Graph Algorithms: Minimum Spanning Trees (KT 4.5, KT 4.6) | HW4 & Task2 Deadline |
| Jun 25 (Thu) | Graph Algorithms: Shortest Paths (KT 4.4) | ||
| 6 | Jun 30 (Tue) | NP-Completeness (KT 8.4) | P2 Deadline |
| Jul 02 (Thu) | Polynomial Time Reductions (KT 8.5) and Review | ||
| Jul 03 (Fri) | Final-Exam (3 hours, to be completed within a 24-hour window) |
| HWs/Projects | Releasing Date | Deadline |
|---|---|---|
| HW1 | May 26 | Tue, Jun 02 |
| HW2 | Jun 02 | Tue, Jun 09 |
| HW3 | Jun 09 | Tue, Jun 16 |
| HW4 | Jun 16 | Tue, Jun 23 |
| Project 1 | Jun 09 | Tue, Jun 16 |
| Project 2 | Jun 23 | Tue, Jun 30 |
| Task 1 | May 26 | Tue, Jun 02 |
| Task 2 | Jun 16 | Tue, Jun 23 |
Deadlines: All assignment deadlines are on Tuesday at 11:59 PM EST. Expectations will be clearly stated when assignments are released, including the duration of each assignment. Please pay close attention to the allotted time and begin early.
Submission Format: Submit typed PDF files for homework. You may use any word processor of your choice; Microsoft Word and LaTeX are recommended. For web-based LaTeX editing, you may use platforms such as Overleaf.
Submission Platform: All assignments will be submitted and returned via UBlearns.