Daniel Alabi - RankMe

38 papers A* 6Journal 28Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	When Does Quantum Differential Privacy Compose? CoRR Daniel Alabi, Theshani Nuradha
2025	J	`jnl`	Efficiently Attacking Memorization Scores. CoRR Tue Do, Varun Chandrasekaran, Daniel Alabi
2025	J	`jnl`	Inaccessible Entropy for Watermarking Generative Agents. IACR Cryptol. ePrint Arch. Daniel Alabi, Lav R. Varshney
2025	—	`conf`	Privacy and Security in Distributed Data Markets. SIGMOD Conference Companion Daniel Alabi, Sainyam Galhotra, Shagufta Mehnaz, Zeyu Song, Eugene Wu
2025	J	`jnl`	Privacy and Security in Distributed Data Markets. IACR Cryptol. ePrint Arch. Daniel Alabi, Sainyam Galhotra, Shagufta Mehnaz, Zeyu Song, Eugene Wu
2025	J	`jnl`	Representation of Inorganic Synthesis Reactions and Prediction: Graphical Framework and Datasets. CoRR Samuel Andrello, Daniel Alabi, Simon J. L. Billinge
2025	J	`jnl`	Scalable Multiterminal Key Agreement via Error-Correcting Codes. CoRR Benjamin D. Kim, Daniel Alabi, Lav R. Varshney
2025	—	`conf`	Separating Graph Generative Models via Degree Distributions. KDD (2) Daniel Alabi, Dimitris Kalimeris
2025	J	`jnl`	Suna: Scalable Causal Confounder Discovery over Relational Data. Proc. VLDB Endow. Jiaxiang Liu, Siyuan Xia, Daniel Alabi, Eugene Wu
2025	J	`jnl`	Watermarking Discrete Diffusion Language Models. CoRR Avi Bagchi, Akhil Bhimaraju, Moulik Choraria, Daniel Alabi, Lav R. Varshney
2024	J	`jnl`	EmpireDB: Data System to Accelerate Computational Sciences. CoRR Daniel Alabi, Eugene Wu
2024	J	`jnl`	Lecture Notes from the NaijaCoder Summer Camp. CoRR Daniel Alabi, Joseph Ekpenyong, Alida Monaco
2024	—	`conf`	NaijaCoder: Participatory Design for Early Algorithms Education in the Global South. SIGCSE (1) Daniel Alabi, Atinuke Adegbile, Lekan Afuye, Philip Abel, Alida Monaco
2023	J	`jnl`	Bounded Space Differentially Private Quantiles. Trans. Mach. Learn. Res. Daniel Alabi, Omri Ben-Eliezer, Anamay Chaturvedi
2023	J	`jnl`	Degree Distribution Identifiability of Stochastic Kronecker Graphs. CoRR Daniel Alabi, Dimitris Kalimeris
2023	J	`jnl`	Differentially Private Hypothesis Testing for Linear Regression. J. Mach. Learn. Res. Daniel Alabi, Salil P. Vadhan
2023	J	`jnl`	NaijaCoder: Participatory Design for Early Algorithms Education in the Global South. CoRR Daniel Alabi, Atinuke Adegbile, Lekan Afuye, Philip Abel, Alida Monaco
2023	J	`jnl`	Privacy Budget Tailoring in Private Data Analysis. Trans. Mach. Learn. Res. Daniel Alabi, Chris Wiggins
2023	A*	`conf`	Privately Estimating a Gaussian: Efficient, Robust, and Optimal. STOC Daniel Alabi, Pravesh K. Kothari, Pranay Tankala, Prayaag Venkat, Fred Zhang
2023	J	`jnl`	Saibot: A Differentially Private Data Search Platform. CoRR Zezhou Huang, Jiaxiang Liu, Daniel Alabi, Raul Castro Fernandez, Eugene Wu
2023	J	`jnl`	Saibot: A Differentially Private Data Search Platform. Proc. VLDB Endow. Zezhou Huang, Jiaxiang Liu, Daniel Alabi, Raul Castro Fernandez, Eugene Wu
2022	J	`jnl`	Bounded Space Differentially Private Quantiles. CoRR Daniel Alabi, Omri Ben-Eliezer, Anamay Chaturvedi
2022	J	`jnl`	Differentially Private Simple Linear Regression. Proc. Priv. Enhancing Technol. Daniel Alabi, Audra McMillan, Jayshree Sarathy, Adam D. Smith, Salil P. Vadhan
2022	A*	`conf`	Hypothesis Testing for Differentially Private Linear Regression. NeurIPS Daniel Alabi, Salil P. Vadhan
2022	J	`jnl`	Hypothesis Testing for Differentially Private Linear Regression. CoRR Daniel Alabi, Salil P. Vadhan
2022	A*	`conf`	Private Rank Aggregation in Central and Local Models. AAAI Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Privately Estimating a Gaussian: Efficient, Robust and Optimal. CoRR Daniel Alabi, Pravesh K. Kothari, Pranay Tankala, Prayaag Venkat, Fred Zhang
2021	J	`jnl`	Private Rank Aggregation in Central and Local Models. CoRR Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2020	J	`jnl`	Differentially Private Simple Linear Regression. CoRR Daniel Alabi, Audra McMillan, Jayshree Sarathy, Adam D. Smith, Salil P. Vadhan
2019	A*	`conf`	Learning to Prune: Speeding up Repeated Computations. COLT Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
2019	J	`jnl`	Learning to Prune: Speeding up Repeated Computations. CoRR Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
2019	J	`jnl`	The Cost of a Reductions Approach to Private Fair Optimization. CoRR Daniel Alabi
2018	A*	`conf`	Unleashing Linear Optimizers for Group-Fair Learning and Optimization. COLT Daniel Alabi, Nicole Immorlica, Adam Kalai
2018	J	`jnl`	When optimizing nonlinear objectives is no harder than linear objectives. CoRR Daniel Alabi, Nicole Immorlica, Adam Tauman Kalai
2017	J	`jnl`	Learning Certifiably Optimal Rule Lists for Categorical Data. CoRR Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi, Margo I. Seltzer, Cynthia Rudin
2017	J	`jnl`	Learning Certifiably Optimal Rule Lists for Categorical Data. J. Mach. Learn. Res. Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi, Margo I. Seltzer, Cynthia Rudin
2017	A*	`conf`	Learning Certifiably Optimal Rule Lists. KDD Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi, Margo I. Seltzer, Cynthia Rudin
2016	—	`conf`	PFunk-H: approximate query processing using perceptual models. HILDA@SIGMOD Daniel Alabi, Eugene Wu