TY - GEN
T1 - Improving the Lower Bound for the Union-closed Sets Conjecture via Conditionally IID Coupling
AU - Liu, Jingbo
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Recently, Gilmer proved the first constant lower bound for the union-closed sets conjecture via an information-theoretic argument. The heart of the argument is an entropic inequality involving the OR function of two i.i.d. binary vectors, and the best constant obtainable through the i.i.d. coupling is $\frac{{3 - \sqrt 5 }}{2} \approx 0.38197$. Sawin demonstrated that the bound can be strictly improved by considering a convex combination of the i.i.d. coupling and the max-entropy coupling, and the best constant obtainable through this approach is around 0.38234, as evaluated by Yu and Cambie. In this work we show analytically that the bound can be further strictly improved by considering another class of coupling under which the two binary sequences are i.i.d. conditioned on an auxiliary random variable. We also provide a new class of bounds in terms of finite-dimensional optimization. Additional results about evaluations of the bounds can be found in arXiv:2306.08824
AB - Recently, Gilmer proved the first constant lower bound for the union-closed sets conjecture via an information-theoretic argument. The heart of the argument is an entropic inequality involving the OR function of two i.i.d. binary vectors, and the best constant obtainable through the i.i.d. coupling is $\frac{{3 - \sqrt 5 }}{2} \approx 0.38197$. Sawin demonstrated that the bound can be strictly improved by considering a convex combination of the i.i.d. coupling and the max-entropy coupling, and the best constant obtainable through this approach is around 0.38234, as evaluated by Yu and Cambie. In this work we show analytically that the bound can be further strictly improved by considering another class of coupling under which the two binary sequences are i.i.d. conditioned on an auxiliary random variable. We also provide a new class of bounds in terms of finite-dimensional optimization. Additional results about evaluations of the bounds can be found in arXiv:2306.08824
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U2 - 10.1109/CISS59072.2024.10480167
DO - 10.1109/CISS59072.2024.10480167
M3 - Conference contribution
AN - SCOPUS:85190626744
T3 - 2024 58th Annual Conference on Information Sciences and Systems, CISS 2024
BT - 2024 58th Annual Conference on Information Sciences and Systems, CISS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 58th Annual Conference on Information Sciences and Systems, CISS 2024
Y2 - 13 March 2024 through 15 March 2024
ER -