Lectures related to Differentiable Ranking and Sorting

AI for Science

Explores fundamental principles in scientific research, the impact of computers, numerical algorithms, and deep learning in solving high-dimensional problems.

Socially-aware Artificial Intelligence for Last-mile Mobility

Explores socially-aware AI for last-mile mobility, focusing on understanding social etiquettes, anticipating behaviors, and forecasting crowd movements.

Introduction to Algorithms: Course Overview and Basics

Introduces the CS-250 Algorithms course, covering its structure, objectives, and key topics in algorithmic problem-solving.

Optimization Algorithms: Greedy Approach

Explores optimization problems and greedy algorithms for efficient decision-making.

Algorithms in Computer Science: Search and Sort Techniques

Provides an overview of essential search and sort algorithms in computer science.

Veridical Data Science: Responsible, Reliable, Reproducible

By Prof. Bin Yu explores veridical data science, emphasizing responsible, reliable, and reproducible data analysis and decision-making.

Gradient-Based Algorithms in High-Dimensional Learning

Provides insights on gradient-based algorithms, deep learning mysteries, and the challenges of non-convex problems.

Algorithms: Summary of the week

Covers algorithms for searching, sorting, optimization, and the Halting Problem.

Safe Machine Learning: Cryptographic Opportunities

Explores the intersection between machine learning and cryptography, focusing on safe machine learning through cryptographic tools and models.

Entropy and Algorithms: Applications in Sorting and Weighing

Covers the application of entropy in algorithms, focusing on sorting and decision-making strategies.

Introduction to Algorithms: Basics and Importance

Covers the basics of algorithms, the importance of studying them, data structures, and the impact of algorithms on various fields.

Computation & Algorithms II: Binary Search and Merge Sort

Explores binary search, merge sort, recursion in algorithms, Fibonacci numbers, and dynamic programming.

Search Algorithms: Two Examples

Covers basic algorithm ingredients, search algorithms, control structures, and algorithm correctness.

Hashing & Sorting

Explores hashing techniques like static, extendible, and linear hashing, along with sorting methods such as external merge sort and B+ trees.

Merge Sort: Sorting Algorithm

Explains the merge sort algorithm, its correctness, and time complexity compared to other sorting algorithms.

Complexity & Induction: Algorithms & Proofs

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Data-Driven Modeling of Haemodynamics in Vascular Flows

Explores data-driven modeling of haemodynamics in vascular flows, focusing on computational challenges, reduced order modeling, FSI problems, and neural network applications.

Matrix Factorization: Optimization and Evaluation

Explores matrix factorization optimization, evaluation methods, and challenges in recommendation systems.

Algorithmic Challenges: Solutions and Optimization

Explores algorithmic challenges, time complexity, optimization, recursion, and probability calculations.

Gradient Descent

Covers the concept of gradient descent, a universal algorithm used to find the minimum of a function.