Insu Han - RankMe

42 papers A* 15A 1Journal 25Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DNACHUNKER: Learnable Tokenization for DNA Language Models. CoRR Taewon Kim, Jihwan Shin, Hyomin Kim, Youngmok Jung, Jonghoon Lee, Won-Chul Lee, Insu Han, Sungsoo Ahn
2026	J	`jnl`	KnapSpec: Self-Speculative Decoding via Adaptive Layer Selection as a Knapsack Problem. CoRR Seongjin Cha, Gyuwan Kim, Dongsu Han, Tao Yang, Insu Han
2025	J	`jnl`	A Dual Power Mode Q/V-Band SiGe HBT Cascode Power Amplifier With a Novel Reconfigurable Four-Way Wilkinson Power Combiner Balun. IEEE Trans. Circuits Syst. II Express Briefs Insu Han, Hanjung Lee, Seong-Mo Moon, Inchan Ju
2025	J	`jnl`	BalanceKV: KV Cache Compression through Discrepancy Theory. CoRR Insu Han, Michael Kapralov, Ekaterina Kochetkova, Kshiteej Sheth, Amir Zandieh
2025	J	`jnl`	Design of a Compact, Highly Efficient, and High-Power Q-/V-Band SiGe HBT Cascode Power Amplifier With a Four-Way Wilkinson Power Combiner Balun. IEEE J. Solid State Circuits Hanjung Lee, Insu Han, Inchan Ju
2025	—	`conf`	Mamba Drafters for Speculative Decoding. EMNLP (Findings) Daewon Choi, Seunghyuk Oh, Saket Dingliwal, Jihoon Tack, Kyuyoung Kim, Woomin Song, Seojin Kim, Insu Han, Jinwoo Shin, Aram Galstyan, Shubham Katiyar, Sravan Babu Bodapati
2025	J	`jnl`	Mamba Drafters for Speculative Decoding. CoRR Daewon Choi, Seunghyuk Oh, Saket Dingliwal, Jihoon Tack, Kyuyoung Kim, Woomin Song, Seojin Kim, Insu Han, Jinwoo Shin, Aram Galstyan, Shubham Katiyar, Sravan Babu Bodapati
2025	J	`jnl`	PolarQuant: Quantizing KV Caches with Polar Transformation. CoRR Insu Han, Praneeth Kacham, Amin Karbasi, Vahab Mirrokni, Amir Zandieh
2025	A*	`conf`	QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overhead. AAAI Amir Zandieh, Majid Daliri, Insu Han
2024	A*	`conf`	Cell2Sentence: Teaching Large Language Models the Language of Biology. ICML Daniel LeVine, Syed Asad Rizvi, Sacha Lévy, Nazreen Pallikkavaliyaveetil, David Zhang, Xingyu Chen, Sina Ghadermarzi, Ruiming Wu, Zihe Zheng, Ivan Vrkic, Anna Zhong, Daphne Raskin, Insu Han, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro, Amin Karbasi, Rahul Madhav Dhodapkar, David van Dijk
2024	A*	`conf`	HyperAttention: Long-context Attention in Near-Linear Time. ICLR Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
2024	J	`jnl`	QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overhead. CoRR Amir Zandieh, Majid Daliri, Insu Han
2024	J	`jnl`	SubGen: Token Generation in Sublinear Time and Memory. CoRR Amir Zandieh, Insu Han, Vahab Mirrokni, Amin Karbasi
2023	J	`jnl`	HyperAttention: Long-context Attention in Near-Linear Time. CoRR Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
2023	A*	`conf`	KDEformer: Accelerating Transformers via Kernel Density Estimation. ICML Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi
2023	J	`jnl`	KDEformer: Accelerating Transformers via Kernel Density Estimation. CoRR Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi
2023	A*	`conf`	Near Optimal Reconstruction of Spherical Harmonic Expansions. NeurIPS Amir Zandieh, Insu Han, Haim Avron
2022	A*	`conf`	Fast Neural Kernel Embeddings for General Activations. NeurIPS Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
2022	J	`jnl`	Fast Neural Kernel Embeddings for General Activations. CoRR Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
2022	J	`jnl`	Near Optimal Reconstruction of Spherical Harmonic Expansions. CoRR Amir Zandieh, Insu Han, Haim Avron
2022	A*	`conf`	Random Gegenbauer Features for Scalable Kernel Methods. ICML Insu Han, Amir Zandieh, Haim Avron
2022	J	`jnl`	Random Gegenbauer Features for Scalable Kernel Methods. CoRR Insu Han, Amir Zandieh, Haim Avron
2022	A*	`conf`	Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. ICML Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi
2022	J	`jnl`	Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. CoRR Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi
2022	A*	`conf`	Scalable Sampling for Nonsymmetric Determinantal Point Processes. ICLR Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi
2022	J	`jnl`	Scalable Sampling for Nonsymmetric Determinantal Point Processes. CoRR Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi
2021	J	`jnl`	Random Features for the Neural Tangent Kernel. CoRR Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
2021	A*	`conf`	Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. ICLR Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
2021	A*	`conf`	Scaling Neural Tangent Kernels via Sketching and Random Features. NeurIPS Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
2021	J	`jnl`	Scaling Neural Tangent Kernels via Sketching and Random Features. CoRR Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
2020	A	`conf`	MAP Inference for Customized Determinantal Point Processes via Maximum Inner Product Search. AISTATS Insu Han, Jennifer Gillenwater
2020	A*	`conf`	Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix. ICML Insu Han, Haim Avron, Jinwoo Shin
2020	J	`jnl`	Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. CoRR Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
2019	J	`jnl`	Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix. CoRR Insu Han, Haim Avron, Jinwoo Shin
2018	J	`jnl`	Optimizing Spectral Sums using Randomized Chebyshev Expansions. CoRR Insu Han, Haim Avron, Jinwoo Shin
2018	A*	`conf`	Stochastic Chebyshev Gradient Descent for Spectral Optimization. NeurIPS Insu Han, Haim Avron, Jinwoo Shin
2017	J	`jnl`	Approximating Spectral Sums of Large-Scale Matrices using Stochastic Chebyshev Approximations. SIAM J. Sci. Comput. Insu Han, Dmitry Malioutov, Haim Avron, Jinwoo Shin
2017	A*	`conf`	Faster Greedy MAP Inference for Determinantal Point Processes. ICML Insu Han, Prabhanjan Kambadur, KyoungSoo Park, Jinwoo Shin
2017	J	`jnl`	Faster Greedy MAP Inference for Determinantal Point Processes. CoRR Insu Han, Prabhanjan Kambadur, KyoungSoo Park, Jinwoo Shin
2016	J	`jnl`	Approximating the Spectral Sums of Large-scale Matrices using Chebyshev Approximations. CoRR Insu Han, Dmitry Malioutov, Haim Avron, Jinwoo Shin
2015	J	`jnl`	Large-scale Log-determinant Computation through Stochastic Chebyshev Expansions. CoRR Insu Han, Dmitry Malioutov, Jinwoo Shin
2015	A*	`conf`	Large-scale log-determinant computation through stochastic Chebyshev expansions. ICML Insu Han, Dmitry Malioutov, Jinwoo Shin