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Explore a conference talk by Yiduo Ke on the groundbreaking algorithm for solving the bin packing problem within 1 + ε in linear time. Delve into this well-known optimization challenge in theoretical computer science, where items of varying sizes must be efficiently packed into a limited number of fixed-capacity bins. Discover the polynomial-time asymptotic approximation scheme developed by De la Vega and Lueker, which revolutionized the approach to this problem. Learn about the wide-ranging applications of bin packing, from practical scenarios like filling suitcases and loading trucks to technological uses in file backups and chip design. Gain insights from Yiduo Ke, a PhD candidate in theoretical computer science at Northwestern University and summer research intern at Espresso AI, as she presents this complex topic in an accessible manner.