Revisiting Zero-Rate Bounds on the Reliability Function of Discrete Memoryless Channels. - Marco Bondaschi; Marco Dalai (ISIT, 2020)

Zero-rate Reliability Function for Mismatched Decoding. - Marco Bondaschi; Albert Guillén i Fàbregas; Marco Dalai (ISIT, 2021)

A Revisitation of Low-Rate Bounds on the Reliability Function of Discrete Memoryless Channels for List Decoding. - Marco Bondaschi; Marco Dalai (IEEE Trans. Inf. Theory, 2022)

Mismatched Decoding Reliability Function at Zero Rate. - Marco Bondaschi; Albert Guillén i Fàbregas; Marco Dalai (IEEE Trans. Inf. Theory, 2022)

LASER: Linear Compression in Wireless Distributed Optimization. - Ashok Vardhan Makkuva; Marco Bondaschi; Thijs Vogels; Martin Jaggi; Hyeji Kim; Michael Gastpar (ICML, 2024)

Batch Universal Prediction. - Marco Bondaschi; Michael Gastpar (ISIT, 2024)

Local to Global: Learning Dynamics and Effect of Initialization for Transformers. - Ashok Vardhan Makkuva; Marco Bondaschi; Adway Girish; Alliot Nagle; Hyeji Kim; Michael Gastpar; Chanakya Ekbote (NeurIPS, 2024)

Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models. - Alliot Nagle; Adway Girish; Marco Bondaschi; Michael Gastpar; Ashok Vardhan Makkuva; Hyeji Kim (NeurIPS, 2024)

Transformers on Markov data: Constant depth suffices. - Nived Rajaraman; Marco Bondaschi; Ashok Vardhan Makkuva; Kannan Ramchandran; Michael Gastpar (NeurIPS, 2024)

Attention with Markov: A Framework for Principled Analysis of Transformers via Markov Chains. - Ashok Vardhan Makkuva; Marco Bondaschi; Adway Girish; Alliot Nagle; Martin Jaggi; Hyeji Kim; Michael Gastpar (CoRR, 2024)

Batch Normalization Decomposed. - Ido Nachum; Marco Bondaschi; Michael Gastpar; Anatoly Khina (CoRR, 2024)

Attention with Markov: A Curious Case of Single-layer Transformers. - Ashok Vardhan Makkuva; Marco Bondaschi; Adway Girish; Alliot Nagle; Martin Jaggi; Hyeji Kim; Michael Gastpar (ICLR, 2025)

From Markov to Laplace: How Mamba In-Context Learns Markov Chains. - Marco Bondaschi; Nived Rajaraman; Xiuying Wei; Kannan Ramchandran; Razvan Pascanu; Caglar Gulcehre; Michael Gastpar; Ashok Vardhan Makkuva (CoRR, 2025)

Alpha-NML Universal Predictors. - Marco Bondaschi; Michael Gastpar (IEEE Trans. Inf. Theory, 2025)

What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains. - Chanakya Ekbote; Marco Bondaschi; Nived Rajaraman; Jason D. Lee; Michael Gastpar; Ashok Vardhan Makkuva; Paul Pu Liang (CoRR, 2025)

The Conditional Regret-Capacity Theorem for Batch Universal Prediction. - Marco Bondaschi; Michael Gastpar (CoRR, 2025)