Kailash Budhathoki

31 papers A* 5A 5C 1Journal 16Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	When LLMs get significantly worse: A statistical approach to detect model degradations. CoRR Jonas M. Kübler, Kailash Budhathoki, Matthäus Kleindessner, Xiong Zhou, Junming Yin, Ashish Khetan, George Karypis
2025	J	`jnl`	A Proximal Operator for Inducing 2:4-Sparsity. CoRR Jonas M. Kübler, Yu-Xiang Wang, Shoham Sabach, Navid Ansari, Matthäus Kleindessner, Kailash Budhathoki, Volkan Cevher, George Karypis
2025	J	`jnl`	A Proximal Operator for Inducing 2:4-Sparsity. Trans. Mach. Learn. Res. Jonas M. Kübler, Yu-Xiang Wang, Shoham Sabach, Navid Ansari, Matthäus Kleindessner, Kailash Budhathoki, Volkan Cevher, George Karypis
2025	J	`jnl`	Block-Diagonal LoRA for Eliminating Communication Overhead in Tensor Parallel LoRA Serving. CoRR Xinyu Wang, Jonas M. Kübler, Kailash Budhathoki, Yida Wang, Matthäus Kleindessner
2024	J	`jnl`	DoWhy-GCM: An Extension of DoWhy for Causal Inference in Graphical Causal Models. J. Mach. Learn. Res. Patrick Blöbaum, Peter Götz, Kailash Budhathoki, Atalanti-Anastasia Mastakouri, Dominik Janzing
2024	A*	`conf`	Inference Optimization of Foundation Models on AI Accelerators. KDD Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis
2024	J	`jnl`	Inference Optimization of Foundation Models on AI Accelerators. CoRR Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis
2024	J	`jnl`	LLM-Rank: A Graph Theoretical Approach to Pruning Large Language Models. CoRR David Hoffmann, Kailash Budhathoki, Matthäus Kleindessner
2024	—	`conf`	Meaningful Causal Aggregation and Paradoxical Confounding. CLeaR Yuchen Zhu, Kailash Budhathoki, Jonas M. Kübler, Dominik Janzing
2024	A	`conf`	Quantifying intrinsic causal contributions via structure preserving interventions. AISTATS Dominik Janzing, Patrick Blöbaum, Atalanti-Anastasia Mastakouri, Philipp Michael Faller, Lenon Minorics, Kailash Budhathoki
2023	C	`conf`	Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. AIES Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell
2023	J	`jnl`	Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. CoRR Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell
2023	J	`jnl`	Meaningful Causal Aggregation and Paradoxical Confounding. CoRR Yuchen Zhu, Kailash Budhathoki, Jonas M. Kübler, Dominik Janzing
2022	A*	`conf`	Causal structure-based root cause analysis of outliers. ICML Kailash Budhathoki, Lenon Minorics, Patrick Blöbaum, Dominik Janzing
2022	J	`jnl`	DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models. CoRR Patrick Blöbaum, Peter Götz, Kailash Budhathoki, Atalanti-Anastasia Mastakouri, Dominik Janzing
2022	J	`jnl`	Explaining the root causes of unit-level changes. CoRR Kailash Budhathoki, George Michailidis, Dominik Janzing
2021	A	`conf`	Discovering Reliable Causal Rules. SDM Kailash Budhathoki, Mario Boley, Jilles Vreeken
2021	A	`conf`	Why did the distribution change? AISTATS Kailash Budhathoki, Dominik Janzing, Patrick Blöbaum, Hoiyi Ng
2021	J	`jnl`	Why did the distribution change? CoRR Kailash Budhathoki, Dominik Janzing, Patrick Blöbaum, Hoiyi Ng
2020	—	`—`	Causal inference on discrete data. Kailash Budhathoki
2020	J	`jnl`	Discovering Reliable Causal Rules. CoRR Kailash Budhathoki, Mario Boley, Jilles Vreeken
2019	J	`jnl`	Causal structure based root cause analysis of outliers. CoRR Dominik Janzing, Kailash Budhathoki, Lenon Minorics, Patrick Blöbaum
2018	A*	`conf`	Accurate Causal Inference on Discrete Data. ICDM Kailash Budhathoki, Jilles Vreeken
2018	A	`conf`	Causal Inference on Event Sequences. SDM Kailash Budhathoki, Jilles Vreeken
2018	J	`jnl`	Origo: causal inference by compression. Knowl. Inf. Syst. Kailash Budhathoki, Jilles Vreeken
2018	—	`conf`	Ranking the Teams in European Football Leagues with Agony. MLSA@PKDD/ECML Stefan Neumann, Julian Ritter, Kailash Budhathoki
2017	J	`jnl`	Causal Inference by Stochastic Complexity. CoRR Kailash Budhathoki, Jilles Vreeken
2017	A	`conf`	Correlation by Compression. SDM Kailash Budhathoki, Jilles Vreeken
2017	A*	`conf`	MDL for Causal Inference on Discrete Data. ICDM Kailash Budhathoki, Jilles Vreeken
2016	A*	`conf`	Causal Inference by Compression. ICDM Kailash Budhathoki, Jilles Vreeken
2015	—	`conf`	The Difference and the Norm - Characterising Similarities and Differences Between Databases. ECML/PKDD (2) Kailash Budhathoki, Jilles Vreeken