A Proof of the Fisher Information Inequality via a Data Processing Argument
By Ram Zamir. 1998
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- Chuan Guo
- Peter Kairouz
- Leighton Pate Barnes
- Ayfer Özgür
- Pramod Viswanath
- L. V. D. van der Maaten
- Nicholas Carlini
- Yoshua Bengio
Citations in the corpus
- Learning Distributions from their Samples under Communication Constraints (2019, methodology): “The upper bound Tr ( I M ( θ )) ≤ Tr ( I X ( θ )) follows easily from the data processing inequality for Fisher information [11].”
- Bounding Training Data Reconstruction in Private (Deep) Learning (2022, background): “…model h ← A ( D train ) is a deterministic function of only the initial parameters w 0 and the observed gradients ¯ g 1 , . . . any , ¯ g T without other access to z , hence by the post-processing inequality for Fisher information (Zamir, 1998), we get I h ( z ) I w 0 , ¯ g 1 ,..., ¯ g T ( z ) .”
- Lower Bounds for Learning Distributions under Communication Constraints via Fisher Information (2019, methodology): “To finish the proof of Theorem 1, note that the upper bound Tr(IM (θ)) ≤ Tr(IX(θ)) follows easily from the data processing inequality for Fisher information Zamir (1998).”
- Ridge regression and asymptotic minimax estimation over spheres of growing dimension (2016, background): “Lemma B.5 (Stam’s inequality; this version due to Zamir [53]).”
- An Extremal Inequality Motivated by Multiterminal Information-Theoretic Problems (2007, methodology): “An interesting estimation-theoretic proof using the data processing inequality for Fisher information was given by Zamir [11].”
- Subdiffraction incoherent optical imaging via spatial-mode demultiplexing (2016, background): “[42] Ram Zamir, “A proof of the Fisher information inequality via a data processing argument,” IEEE Transactions on Information Theory 44, 1246–1250 (1998).”
- Minimax Bounds for Distributed Logistic Regression (2019, background): “The first term in the max term of each lemma is a simple consequence of the data processing inequality for Fisher information (Zamir, 1998), so we will focus on the other terms.”
- An Extremal Inequality Motivated by Multiterminal Information Theoretic Problems (2006, background): “An interesting estimation theoretic proof of FII was given by Zamir [13].”