145c28cd4b1df9b426990fd68045f4f7-Supplemental-Conference.pdf
–Neural Information Processing Systems
Therefore, take an arbitrary k { 0, 1,...,n } and k Proof of Lemma 2. By Lemma 1, we have λ( π Proof of Lemma 3. We prove this lemma by backward induction on k . We want to show that our statement holds for k = K . Proof of Theorem 2. First fix the underlying parameters of the RMJ-based ranking model We break the rest of the proof into two parts: the "if" part and the "only if" part. We provide the proof details in Appendix B.2. Lemma 4 ˆ q q We claim that it does not hold that ˆ π e almost surely as T . The rest of proof consists of two steps.
Neural Information Processing Systems
Nov-13-2025, 10:16:35 GMT